Web based Decision Support System (DSS) for evaluating mining company performance based on quantitative parameters

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WEB BASED DECISION SUPPORT SYSTEM (DSS) FOR

EVALUATING MINING COMPANY PERFORMANCE

BASED ON QUANTITATIVE PARAMETERS

By

Iksal Yanuarsyah

G.051030011

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2005


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I, Mr. Iksal Yanuarsyah, herewith declare the thesis title:

Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based on Quantitative Parameters

Contains correct results come in from my own work and it has not been published ever before. All data sources and information have used factual and clear methods in this research has been examined for its factualness.

Bogor, October 2005

Iksal Yanuarsyah


(3)

IKSAL YANUARSYAH, Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based On Quantitative Parameters. Under the direction of KUDANG B. SEMINAR and IDUNG RISDIYANTO.

Objective assessment for company performance can be conducted comprehensively of obedience and implementation of good mining practice aspects, and transparently with involving stakeholders. Mining Integrative and Comprehensive Evaluation System development is expected to assess company performance considering good mining practice which has several evaluation criteria formulated with parameters and variables in mining activity aspects, performance evaluation of mining company can be obtained using decision support system (DSS) approach. Consider to good mining practice, the processes of evaluation mining company performance will be visualized through internet or

World Wide Web (WWW) suppose that stakeholders as decision makers or web users faced those information up to date with any kinds of procedures such user log in, data input, data query, weighting variables and data output as integrative and comprehensive information and interactively.

The objective of this study is to construct mining company evaluation system based on quantitative parameters (MICES-Quan) through web in term of good mining practice. The scope of research is around mining company (mine or coal) with subject of mining parameters consider to mining engineering and mining environment protection, the operation phases refers only to production or exploitation phase and the time / period of evaluation will be conducted in each year of production (exploitation) or in each three months (quarterly) of production (exploitation).

This research architecture consists of four tiers such web client (1), web server (2), application server (3) and DBMS server (4). This research used perspective analysis and weighting and scoring also system development implementation through prototype visualization.

Based on the result, there have several input variables (i.e. air quality monitoring, water quality monitoring, production and processing, environment cost and mining operation) which are important influence to the other variables (i.e. cutting, cover soil peeling, shipping, reserve addition, washing and purifying, reclamation stockpile, mining environment, and sprout soil peeling). Scoring and weighting gave a systematic calculation of parameters to achieve the final evaluation. The result of MICES-Quan implementation consists of database implementation, DSS Tool implementation, and web implementation. The combination and connectivity is running well with local server test-drive.

This evaluation system can be used as an alternative way o evaluate company performance with proposed system offer integrated way of evaluating considering quantitative parameters.

Keyword: Good Mining Practice, Mining Engineering, Mining Environment Monitoring, Perspective Analysis, Weighting and Scoring, Web Client, Web Server, Application Server, Database and Implementation.


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W

EB

B

ASED

D

ECISION

S

UPPORT

S

YSTEM

(DSS)

F

OR

E

VALUATING

M

INING

C

OMPANY

P

ERFORMANCE

B

ASED

ON

Q

UANTITATIVE

P

ARAMETERS

Iksal Yanuarsyah

A Thesis submitted for the degree of Master of Science Of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCE MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

October 2005


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Research Title : Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based on Quantitative Parameters

Student Name : Iksal Yanuarsyah Student ID : G.051030011 / MIT

Study Program : Master in Information Technology for Natural Resources Management

Thesis approved by the Advisory Board:

Dr. Ir. Kudang B. Seminar, MSc Ir. Idung Risdiyanto, MSc Supervisor Co-supervisor

Chairman of Study Program Director for the Graduate Program

Dr. Ir. Tania June Prof. Dr. Ir. Syafrida Manuwoto, M.Sc


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CURRICULUM VITAE

Iksal Yanuarsyah was born in Sumbawa Besar, West Nusa Tenggara, Indonesia at January 28, 1980. He

received his undergraduate diploma from Bogor Agricultural University in 2003 in the field of Forest

Product Technology.

In the year of 2003, Iksal Yanuarsyah received his Post Graduate Diploma in Information Technology for Natural Resources Management and Master of Science in Information Technology for Natural Resources Management from

Bogor Agricultural University Indonesia in 2004 and 2005 respectively. His thesis title was on “Web Based Decision Support System (DSS) For

Evaluating Mining Company Performance Based on Quantitative Parameters”.


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ACKNOWLEDGEMENT

The completion of this research would not have been possible if not through the kind assistance and technical support of several individual and organization.

First of all I would like to grateful thanks to Allah SWT who The Most Merciful and Gracious for blazing me, and allowing me to complete my study.

I would like to express my special appreciation to the following for their invaluable contributions at all stages towards and finishing this thesis, Dr. Kudang B. Seminar, MSc, my primary supervisor who offered me excellent guidance and useful ideas and Ir. Idung Risdiyanto, MSc, the co-supervisor for his constructive discussions, I have the state of the art of decision making on this thesis focuses.

I would like to specially thank to my external examiner supervisor, Dr. Handoko who spent his time in seminar, and gave suggestions in my paper.

I would like to specially thank to experts who work in mining engineering and environment observer such coming from mineral and coal technique director, mining engineering director, mining environment director, and environment consulting for their expertise and information.

I deeply appreciate the effort of MIT staff. I specially appreciate to MIT colleagues for giving me encouragement and supporting, Andes Jayarsa, MSc, Ir. Dede I. Suhendra, Ir. Efo Hadi, Natresc Experts, My Classmate (Mr. Sumaryono and friends), all MIT students and “jojo”(wherever u exist).

Finally, my special gratitude is also extended to my lovely Mom “Salmah M. Nur”, Dad “Abdul Hakik Yahas, S.SOs”, Brother “Syarafuddin” and Sisters “Aliyah Nursanti” and “Yuni Trihasti Pertiwi”, for their prayers, understanding, moral support, patience, encouragement, and everything.

Iksal Yanuarsyah October, 2005


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LIST OF CONTENT

Page

List of Content ... vii

List of Figure ... ix

List of Table ... x

List of Appendixes ... xi

I. INTRODUCTION ... 1

1.1. BACKGROUND ... 1

1.2. OBJECTIVE ... 5

1.3. SCOPE OF RESEARCH ... 5

II. LITERATURE REVIEW ... 7

2.1. GOOD MINING PRACTICE ... 7

2.1.1. Mining Engineering ... 8

2.1.1.1. Exploration ... 8

2.1.1.2. Stipulating of Reserves ... 9

2.1.1.3. Geo-technique Study ... 9

2.1.1.4. Hydrogeology Study ... 10

2.1.1.5. Feasibility Study ... 10

2.1.1.6. Mine Planning ... 10

2.1.1.7. Processing / Purification ... 11

2.1.1.8. Metallurgy Study ... 11

2.1.1.9. Bulk Sampling ... 11

2.1.2. Mining Environment Protection ... 12

2.1.3. Mining Added Value (PNT) ... 12

2.1.4. Mining Standardization ... 13

2.2. DECISION SUPORT SYSTEM ... 14

2.3. INFORMATION SYSTEM ... 15

2.4. SYSTEM DEVELOPMENT ... 17

2.5. INTERNET ... 18

2.5.1. Internet Definition ... 18

2.5.2. Basic Component of Internet ... 19

2.5.2.1. The Client ... 19

2.5.2.2. Web Server ... 20

2.5.2.3. Application Server ... 20

2.5.2.4. Data Server ... 21

III. RESEARCH METHODOLOGY ... 22

3.1. TIME AND LOCATION OF STUDY ... 22

3.2. TYPE OF DATA AND SOURCES ... 22

3.3. METHODS ... 23

3.3.1. System Development Method ... 23

3.3.2. User Need Analysis ... 26

3.3.3. Component Identification ... 27

3.3.3.1. Parameter Identification ... 27


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3.3.4. Decision Support System Analysis ... 33

3.3.4.1. Perspective Analysis ... 34

3.3.4.2. Weighting and Scoring ... 35

IV. RESULT AND DISCUSSION... 39

4.1. ANALYSIS OF DATABASE DESIGN ... 39

4.1.1. Database Design ... 39

a. Process Modeling ... 39

b. Conceptual Model ... 41

c. Logical Model ... 43

d. Physical Model ... 44

4.1.2. User Interface Design ... 46

4.1.3. Web Design ... 47

4.2. ANALYSIS OF SYSTEM EVALUATION ... 50

4.1.1. Perspective analysis ... 50

4.1.2. Weighing and Scoring ... 51

4.3. IMPLEMENTATION ... 54

V. CONCLUSSIONS AND RECOMMENDATIONS ... 63

5.1. CONCLUSIONS ... 63

5.2. RECOMMENDATIONS ... 63


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LIST OF FIGURE

Page

Figure 2.1 Good mining practice paradigm (Suyartono, 2003) ... 8

Figure 2.2 Mining accident data (Suyartono, 2003) ... 12

Figure 2.3 Information system components (O’Brien, 1999) ... 16

Figure 2.4 System Development Life Cycle (O’Brien, 1999) ... 17

Figure 2.5 Prototyping development stages (O’Brien, 1999) ... 18

Figure 2.6 Basic components in Internet GIS (Peng and Tsou, 2003) ... 19

Figure 3.1 Interest area of research ... 22

Figure 3.2 Research scheme ... 24

Figure 3.3 Current system of evaluating mining company performance .... 25

Figure 3.4 Proposed system for evaluating mining performance ... 26

Figure 3.5 DSS scheme of mining performance evaluation ... 33

Figure 3.6 Illustration of influenced factor in quadrant ... 35

Figure 3.7 Architecture of system design ... 37

Figure 3.8 Architecture of web communication process ... 38

Figure 3.9 Web event identification process ... 38

Figure 4.1 MICES-Quan Context Diagram ... 40

Figure 4.2 MICES-Quan DFD Level 1 ... 41

Figure 4.3 MICES-Quan ERD ... 42

Figure 4.4 MICES-Quan information hierarchy ... 48

Figure 4.5 MICES-Quan web design interface ...49

Figure 4.6 Interest level of illustration ... 51

Figure 4.7 My SQL interface ... 55

Figure 4.8 Database sample creation ... 55

Figure 4.9 List of MICES-Quan database ... 56

Figure 4.10 MICES-Quan web “front” interface ...57

Figure 4.11 Mining company performance ... 57

Figure 4.12 Mining company login ... 58

Figure 4.13 Mining company browse data ... 58

Figure 4.14 Mining company adding data ... 59

Figure 4.15 Architecture of system design ... 59

Figure 4.16 evaluation and database stored ... 60

Figure 4.17 MICES-Quan DSS Tool ...61


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WEB BASED DECISION SUPPORT SYSTEM (DSS) FOR

EVALUATING MINING COMPANY PERFORMANCE

BASED ON QUANTITATIVE PARAMETERS

By

Iksal Yanuarsyah

G.051030011

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

2005


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I, Mr. Iksal Yanuarsyah, herewith declare the thesis title:

Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based on Quantitative Parameters

Contains correct results come in from my own work and it has not been published ever before. All data sources and information have used factual and clear methods in this research has been examined for its factualness.

Bogor, October 2005

Iksal Yanuarsyah


(13)

IKSAL YANUARSYAH, Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based On Quantitative Parameters. Under the direction of KUDANG B. SEMINAR and IDUNG RISDIYANTO.

Objective assessment for company performance can be conducted comprehensively of obedience and implementation of good mining practice aspects, and transparently with involving stakeholders. Mining Integrative and Comprehensive Evaluation System development is expected to assess company performance considering good mining practice which has several evaluation criteria formulated with parameters and variables in mining activity aspects, performance evaluation of mining company can be obtained using decision support system (DSS) approach. Consider to good mining practice, the processes of evaluation mining company performance will be visualized through internet or

World Wide Web (WWW) suppose that stakeholders as decision makers or web users faced those information up to date with any kinds of procedures such user log in, data input, data query, weighting variables and data output as integrative and comprehensive information and interactively.

The objective of this study is to construct mining company evaluation system based on quantitative parameters (MICES-Quan) through web in term of good mining practice. The scope of research is around mining company (mine or coal) with subject of mining parameters consider to mining engineering and mining environment protection, the operation phases refers only to production or exploitation phase and the time / period of evaluation will be conducted in each year of production (exploitation) or in each three months (quarterly) of production (exploitation).

This research architecture consists of four tiers such web client (1), web server (2), application server (3) and DBMS server (4). This research used perspective analysis and weighting and scoring also system development implementation through prototype visualization.

Based on the result, there have several input variables (i.e. air quality monitoring, water quality monitoring, production and processing, environment cost and mining operation) which are important influence to the other variables (i.e. cutting, cover soil peeling, shipping, reserve addition, washing and purifying, reclamation stockpile, mining environment, and sprout soil peeling). Scoring and weighting gave a systematic calculation of parameters to achieve the final evaluation. The result of MICES-Quan implementation consists of database implementation, DSS Tool implementation, and web implementation. The combination and connectivity is running well with local server test-drive.

This evaluation system can be used as an alternative way o evaluate company performance with proposed system offer integrated way of evaluating considering quantitative parameters.

Keyword: Good Mining Practice, Mining Engineering, Mining Environment Monitoring, Perspective Analysis, Weighting and Scoring, Web Client, Web Server, Application Server, Database and Implementation.


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W

EB

B

ASED

D

ECISION

S

UPPORT

S

YSTEM

(DSS)

F

OR

E

VALUATING

M

INING

C

OMPANY

P

ERFORMANCE

B

ASED

ON

Q

UANTITATIVE

P

ARAMETERS

Iksal Yanuarsyah

A Thesis submitted for the degree of Master of Science Of Bogor Agricultural University

MASTER OF SCIENCE IN INFORMATION TECHNOLOGY

FOR NATURAL RESOURCE MANAGEMENT

GRADUATE SCHOOL

BOGOR AGRICULTURAL UNIVERSITY

October 2005


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Research Title : Web Based Decision Support System (DSS) For Evaluating Mining Company Performance Based on Quantitative Parameters

Student Name : Iksal Yanuarsyah Student ID : G.051030011 / MIT

Study Program : Master in Information Technology for Natural Resources Management

Thesis approved by the Advisory Board:

Dr. Ir. Kudang B. Seminar, MSc Ir. Idung Risdiyanto, MSc Supervisor Co-supervisor

Chairman of Study Program Director for the Graduate Program

Dr. Ir. Tania June Prof. Dr. Ir. Syafrida Manuwoto, M.Sc


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CURRICULUM VITAE

Iksal Yanuarsyah was born in Sumbawa Besar, West Nusa Tenggara, Indonesia at January 28, 1980. He

received his undergraduate diploma from Bogor Agricultural University in 2003 in the field of Forest

Product Technology.

In the year of 2003, Iksal Yanuarsyah received his Post Graduate Diploma in Information Technology for Natural Resources Management and Master of Science in Information Technology for Natural Resources Management from

Bogor Agricultural University Indonesia in 2004 and 2005 respectively. His thesis title was on “Web Based Decision Support System (DSS) For

Evaluating Mining Company Performance Based on Quantitative Parameters”.


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ACKNOWLEDGEMENT

The completion of this research would not have been possible if not through the kind assistance and technical support of several individual and organization.

First of all I would like to grateful thanks to Allah SWT who The Most Merciful and Gracious for blazing me, and allowing me to complete my study.

I would like to express my special appreciation to the following for their invaluable contributions at all stages towards and finishing this thesis, Dr. Kudang B. Seminar, MSc, my primary supervisor who offered me excellent guidance and useful ideas and Ir. Idung Risdiyanto, MSc, the co-supervisor for his constructive discussions, I have the state of the art of decision making on this thesis focuses.

I would like to specially thank to my external examiner supervisor, Dr. Handoko who spent his time in seminar, and gave suggestions in my paper.

I would like to specially thank to experts who work in mining engineering and environment observer such coming from mineral and coal technique director, mining engineering director, mining environment director, and environment consulting for their expertise and information.

I deeply appreciate the effort of MIT staff. I specially appreciate to MIT colleagues for giving me encouragement and supporting, Andes Jayarsa, MSc, Ir. Dede I. Suhendra, Ir. Efo Hadi, Natresc Experts, My Classmate (Mr. Sumaryono and friends), all MIT students and “jojo”(wherever u exist).

Finally, my special gratitude is also extended to my lovely Mom “Salmah M. Nur”, Dad “Abdul Hakik Yahas, S.SOs”, Brother “Syarafuddin” and Sisters “Aliyah Nursanti” and “Yuni Trihasti Pertiwi”, for their prayers, understanding, moral support, patience, encouragement, and everything.

Iksal Yanuarsyah October, 2005


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LIST OF CONTENT

Page

List of Content ... vii

List of Figure ... ix

List of Table ... x

List of Appendixes ... xi

I. INTRODUCTION ... 1

1.1. BACKGROUND ... 1

1.2. OBJECTIVE ... 5

1.3. SCOPE OF RESEARCH ... 5

II. LITERATURE REVIEW ... 7

2.1. GOOD MINING PRACTICE ... 7

2.1.1. Mining Engineering ... 8

2.1.1.1. Exploration ... 8

2.1.1.2. Stipulating of Reserves ... 9

2.1.1.3. Geo-technique Study ... 9

2.1.1.4. Hydrogeology Study ... 10

2.1.1.5. Feasibility Study ... 10

2.1.1.6. Mine Planning ... 10

2.1.1.7. Processing / Purification ... 11

2.1.1.8. Metallurgy Study ... 11

2.1.1.9. Bulk Sampling ... 11

2.1.2. Mining Environment Protection ... 12

2.1.3. Mining Added Value (PNT) ... 12

2.1.4. Mining Standardization ... 13

2.2. DECISION SUPORT SYSTEM ... 14

2.3. INFORMATION SYSTEM ... 15

2.4. SYSTEM DEVELOPMENT ... 17

2.5. INTERNET ... 18

2.5.1. Internet Definition ... 18

2.5.2. Basic Component of Internet ... 19

2.5.2.1. The Client ... 19

2.5.2.2. Web Server ... 20

2.5.2.3. Application Server ... 20

2.5.2.4. Data Server ... 21

III. RESEARCH METHODOLOGY ... 22

3.1. TIME AND LOCATION OF STUDY ... 22

3.2. TYPE OF DATA AND SOURCES ... 22

3.3. METHODS ... 23

3.3.1. System Development Method ... 23

3.3.2. User Need Analysis ... 26

3.3.3. Component Identification ... 27

3.3.3.1. Parameter Identification ... 27


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3.3.4. Decision Support System Analysis ... 33

3.3.4.1. Perspective Analysis ... 34

3.3.4.2. Weighting and Scoring ... 35

IV. RESULT AND DISCUSSION... 39

4.1. ANALYSIS OF DATABASE DESIGN ... 39

4.1.1. Database Design ... 39

a. Process Modeling ... 39

b. Conceptual Model ... 41

c. Logical Model ... 43

d. Physical Model ... 44

4.1.2. User Interface Design ... 46

4.1.3. Web Design ... 47

4.2. ANALYSIS OF SYSTEM EVALUATION ... 50

4.1.1. Perspective analysis ... 50

4.1.2. Weighing and Scoring ... 51

4.3. IMPLEMENTATION ... 54

V. CONCLUSSIONS AND RECOMMENDATIONS ... 63

5.1. CONCLUSIONS ... 63

5.2. RECOMMENDATIONS ... 63


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LIST OF FIGURE

Page

Figure 2.1 Good mining practice paradigm (Suyartono, 2003) ... 8

Figure 2.2 Mining accident data (Suyartono, 2003) ... 12

Figure 2.3 Information system components (O’Brien, 1999) ... 16

Figure 2.4 System Development Life Cycle (O’Brien, 1999) ... 17

Figure 2.5 Prototyping development stages (O’Brien, 1999) ... 18

Figure 2.6 Basic components in Internet GIS (Peng and Tsou, 2003) ... 19

Figure 3.1 Interest area of research ... 22

Figure 3.2 Research scheme ... 24

Figure 3.3 Current system of evaluating mining company performance .... 25

Figure 3.4 Proposed system for evaluating mining performance ... 26

Figure 3.5 DSS scheme of mining performance evaluation ... 33

Figure 3.6 Illustration of influenced factor in quadrant ... 35

Figure 3.7 Architecture of system design ... 37

Figure 3.8 Architecture of web communication process ... 38

Figure 3.9 Web event identification process ... 38

Figure 4.1 MICES-Quan Context Diagram ... 40

Figure 4.2 MICES-Quan DFD Level 1 ... 41

Figure 4.3 MICES-Quan ERD ... 42

Figure 4.4 MICES-Quan information hierarchy ... 48

Figure 4.5 MICES-Quan web design interface ...49

Figure 4.6 Interest level of illustration ... 51

Figure 4.7 My SQL interface ... 55

Figure 4.8 Database sample creation ... 55

Figure 4.9 List of MICES-Quan database ... 56

Figure 4.10 MICES-Quan web “front” interface ...57

Figure 4.11 Mining company performance ... 57

Figure 4.12 Mining company login ... 58

Figure 4.13 Mining company browse data ... 58

Figure 4.14 Mining company adding data ... 59

Figure 4.15 Architecture of system design ... 59

Figure 4.16 evaluation and database stored ... 60

Figure 4.17 MICES-Quan DSS Tool ...61


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LIST OF TABLE

Page

Table 3.1 General company information ...31

Table 3.2 MySQL 1.3 limitation ... 32

Table 4.1 MICES-Quan logical data model ... 43

Table 4.2 MICES-Quan physical design ... 44 Table 4.3 List of weighted MICES-Quan variables 53


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LIST OF APPENDIXES

Page

Appendix 1 Table of air quality ...65 Appendix 2 Table of cutting ... 66 Appendix 3 Table of environment monitoring ... 67 Appendix 4 Table of mining environment ... 68 Appendix 5 Table of production and processing ... 69 Appendix 6 Table of shipping ... 70 Appendix 7 Table of water quality ... 71 Appendix 8 Table of stockpile ... 72 Appendix 9 Table of user group ...73 Appendix 10 Air quality standard ...74 Appendix 11 MICESQuan DSS tool value ...75 Appendix 12 MICESQuan DSS tool user register ... 76 Appendix 13 Browser / Observer Manual Guide ... 77 Appendix 14 Mining Company Manual Guide ... 79 Appendix 15 Evaluator / Stakeholder Manual Guide ... 81


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I.

INTRODUCTION

1.1. BACKGROUND

Mining is the effort in carrying out mine resources in order to produce valuable product and useful in term of human life necessity manner. In broadest term, it means obtaining process of minerals from earth’s glaze, includi ng the excavation in surface and underground area with using technology development to raise up the economic valuation of the usefulness. Young (1951) states that mining field concerning with discovering and extracting of ores and naturally occurring mineral substances that economically useful.

As one kind of natural resources, mining is classified into a nonrenewable resource with finite number of identified reserve or earth’s deposit which is producing in present time. In other word, mining might be classified as a renewable caused by the resource invention from marginal deposit. Mining is divided into two major classes such minerals and coal. Most minerals are correlated to mineral deposit, which is formed within rocks and coal as dirty fuel which can be extracted for producing energy sources.

Mining activities in Indonesia have been developed since 19th centuries. It started with discovering sites and estimating the potential deposit of mineral materials and coal material. Several activities are followed such exploration, feasibility study, construction, and exploitation or production. Along with the activity, government tried to explore their knowledge to construct the national regulation for mining activities. It was used for starting mining industry development in Indonesia and also to maintain right and duty of mining company for national revenue and local community awareness.


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In the beginning periods after national independence in 1945, the Indonesian government had lacked capital and budget preparation to rise up the development in whole part of Indonesia archipelago. Therefore, government gave the opportunity for foreign investor either domestic to invest their finance in several sectors such as forestry industry, agriculture industry, transportation and communication industry, construction, and mining industry is one major sector that can produce mineral product and energy material. Thus, further hope those can produce saleable product beneficially for national income.

Mining industry development needs technology, skills, and huge amount of capital, so that it is hard and getting difficulties for Indonesia which growing up to explore mineral resources with their own capabilities (Suyartono, 2003). Nowadays, Technology might become one substantial factor in mining industry, mainly as it influences the costs of mineral extraction and purification processing. The quality and price of mining products are affected from international market trading and also related with world consumption of it.

Technology and social changes can also increases in the costs of extraction. Recently environmental regulations have required changes in mining techniques to minimize environmental disruption. These changes have increased the cost of extraction, thus decreasing reserves (Cutter et al, 1991). According to

Suyartono (2003) along with time, the technology development and the invention comes up with pressing of processing cost and metal grade extraction and mineral higher than cost rise effect consequence from moving down of grade rate. For instance, moving down of copper rate from 1,1% in 1970 to 0,8% in this time,


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thus the price of copper and its production costs are falling down with various cycles.

The concept of general mining industry is mine industry which is produce metal, industry entrenchment (non-metal) and coal (energy) also geothermal; emphasizing of “democracy, justice and equal distribution” issues that involves intra generation and inter generation. This concept might be implemented as good as long with involving any kind of stakeholder in partnership optimality manner (Suyartono, 2003).

Good mining practice implementation will avoid a negative environment cases either cases of social community. Environment based management of mining industry should has a pay attention to the principle of work health and safety, environmental impact analysis, added value, community development, standardization, mined closing, and legal aspect. Within these implementations, it can avoid the wasting of mineral and coal resources, reserve or deposit optimality, environment functions protection, and work health and safety guaranteed.

It has the occasion to give an appreciation form for company of mining which have run correct and good mining method. Objective assessment for company performance can be conducted comprehensively of obedience and implementation of good mining practice aspects, and transparently with involving stakeholders. It needs the assessment system throughout accommodative and adequateness.

Mining Integrative and Comprehensive Evaluation System development is expected to assess company performance considering good mining practice time to time with involving stakeholder as according to their responsibility of passing


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network of internet by interactively. Mining company can conduct the reporting of obligation of on schedule, which evaluated directly and quickly by government officer center either local government, and also society and experts who can conduct the assessment and evaluation objectively. Therefore, it will very lighten government in specifying the company criterion with obeying standard, criterion, norm, and also law and regulation applying well for getting award and or sanction.

Consider to good mining practice, which has several evaluation criterion formulated with parameters and variables in mining activity aspects, performance evaluation of mining company can be obtained using decision support system (DSS) approach. Within decision support system, all variables in each parameter will manage through data processing methods to produce recommendations that performs and helps decision makers find out the end result of the performance. It means that DSS make easier in determining a system for evaluation and managing parameters to achieve the goal of decision maker.

The processes of evaluation mining company performance will be visualized through internet or World Wide Web (WWW) suppose that

stakeholders as decision makers or web users faced those information up to date

with any kinds of procedures such user log in, data input, data query, weighting variables and data output as integrative and comprehensive information and interactively. Due to increasing of the number of company who involve in mining business and need more data have to be collected in short time procedures. Thereby, web system is a best choice to solve those procedures with simple and fast procedures for their evaluation.


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1.2. OBJECTIVES

The objectives of this research are to construct mining company evaluation system based on quantitative parameters (MICES-Quan) through web in term of good mining practice. Details of objectives are follows as

1. To conduct evaluation performances of mining company in certain period considering quantitative parameters of good mining practice (mining engineering and mining environment monitoring).

2. To provide web based decision support system for evaluating mining company performance with the graphical user interface. It is expected that the evaluation process will run faster.

3. To improve user awareness of their participation in order to raise of education people in undertaking any decision support related to mining company compliance through web.

1.3. SCOPE OF RESEARCH

Mining activities categorized into a huge scale industrial activity with providing much amount of capital, complex infrastructures, heavy equipments, and recruit large number of employers. The existing of these activities will spread out the opportunity for other supporting sectors such local employer hiring sector, local commerce sector, and local community added value.

In another side of mining activities by using open pit technique or underground mining, explore mineral resources with open land clearing or land exploitation consideration. This activity will affect to the ecosystem balancing and yet environment degradation occurs along the activity period or time


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concession. It also infected to socio and culture community who receive the impact directly.

The scope of this research is around mine subject in term of public mining performance where it will take several kinds of mining company having been activated in Indonesia territorial as a prototypes or samples. According to problems faced mining activity, integrated mining management is needed as long as obeying good mining practice consideration. By doing so, several quantitative parameters of good mining practice include environment quality assessment and mining engineering as the urgent aspects are being monitored. This management handling is evaluated by using comprehensive evaluation involving stakeholder to accomplish the assessment. Therefore, several assumptions that used as constrain of this research follow:

1. Subject of mining parameters consider to mining engineering and mining environment protection.

2. The scope of operation phases in this research refers only to production or exploitation phase.

3. The time / period of evaluation will be conducted in each year of production (exploitation) or in each three months (quarterly) of production (exploitation).


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II.

LITERATURE REVIEW

Developing of web based decision support system for mining company performance evaluation needs fundamental building theory to stretch the system thinking of building thesis structure.

2.1. GOOD MINING PRACTICE

Minerals are substances that come from earth, either from solid rocks or from soils and other deposits (Cutter et al, 1991). Mineral used to indicate any

naturally occurring substance of definite composition and consistent physical properties. In a restricted sense the miner uses it to designate a valuable nonmetalliferous substance (Young, 1951). A mineral is generally defined as any naturally occurring substance of definite chemical composition and consistent physical properties. An ore is a mineral or combination of minerals from which a useful substance, such as a metal, can be extracted and marketed at a price that will recover the costs of mining and processing and yield a profit (Encarta, 2005).

Coal, a combustible organic rock composed primarily of carbon, hydrogen, and oxygen. Coal is burned to produce energy and is used to manufacture steel. It is also an important source of chemicals used to make medicine, fertilizers, pesticides, and other products. Coal comes from ancient plants buried over millions of years in Earth’s c rust, its outermost layer (Encarta, 2005). Coal is the most abundant fossil fuel in the world, with reserves far exceeding those of oil or natural gas (Cutter et al, 1991).

The concept of general mining industry is that mineral mining industry which produces metal, industry excavation material (non-metal) and energy (coal) as well as earth heat have weighting point on the issue of “democratic, justice and


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even distribution” that must involve between generation and intergeneration. This concept can only be done very well if we involve stakeholder interest optimally in the form of association. Practice paradigm in good mining practice (Figure 2.1) develops civilization as a mining activity that fulfills requirements, criteria, principles and norms appropriately so that the exploitation of mineral resources can bring an optimal outcome and minimize the bad effect.

Figure 2.1. Good mining practice paradigm (Suyartono, 2003)

2.1.1. Mining Engineering

Their planning and implementation of correct and good mining techniques make one of the primary factors for the creation of optimality enterprising of mining of public. All components or aspects in mining activity required to study, to be planned and put across, because each aspect to each other are relevant and influencing economics and fluency of mining marketable, as well as influencing well their guaranteed safety of mining, the looking after of environment and also the make-up of prosperity of people especially which there is around mine (Suyartono, 2003).


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2.1.1.1. Exploration

The things required to paid attention in activity of exploration such active effort permission, having mine technique head (mining inspector), exploration program and equipments, socialization of exploration plan, compensatory of farm, drilling, laboratory analysis, finishing required maps like map of geology, map of contour, soil layer map, isopach map, geology report, and reporting to governmental institution (Suyartono, 2003).

2.1.1.2. Stipulating of Reserves

The Reserve is specified into reserve predicted and reserve proven. According to Suyartono (2003), reserve predicted is resource of established and some of mineral resources measured which was storey; level confidence of geology still lower so that economically, mining activity can be done. While proven reserve is mineral resource measured which pursuant to mine feasibility study, all relevant ness factors have fulfilled, so that mining can be conducted economically.

2.1.1.3. Geo-technique Study

According to Suyartono (2003) for the agenda of mining planning method and system and also the election of correct appliance, hence needed study of geo-technique for purposing of determining bevel stability, ramp design, excavability, blasting design, dig step estimation, dig dimension and design, strength of dig materials and ore, entering hole design, heap design of waste, studying of bevel trouble. As for some activities which need to be conducted in knowing characteristic of geo-technique area with activity covered by inside testing,


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laboratory analysis, mapping, study of crack, influence of water, condition and geology of hydrology.

Some studies of geo-technique which was often conducted in mining industry for example: analysis and monitoring of bevel stability, audit of risk analysis and geo-technique, buttress audit and design, model and characterization of rock period (rock mass), and surface stabilization of land; ground, geo-technique criteria for design mine and study of geo-geo-technique for feasibility study.

2.1.1.4. Hydrogeology Study

Suyartono (2003) states that study of hydrogeology depends of the applying method and matter which is obliged to be conducted for the agenda of knowing underground hydrology and surface hydrology, drying of mine, drainage system, quality of water, porosity, zone of aquifer, water captured area, and mine water management.

2.1.1.5. Feasibility Study

Scope in compilation of feasibility study cover some aspects such as technical aspect, work health and safety (K3) aspect, environmental aspect, economic aspect, social law aspect, mined out aspect, and other aspects (Suyartono, 2003).

2.1.1.6. Mine Planning

Planning is determination of clauses, which must be fulfilled from technique site and economics and also technical execution sequence from various sub-activities, which must be executed for the agenda of reaching activity its target (Suyartono, 2003). Furthermore Suyartono (2003) explain referee to the planning needed some factors as considerations for example feasibility study,


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amount of mine and reserves, stripping ratio, maximum boundary deepness of mine, cutting grade off, influence of geology structure, ladder dimension, slice system, dig materials value, production cost, and determination of medium activity of mine.

2.1.1.7. Processing / Purification

Processing and or purification are important aspect here in after mining. This aspect is important also to be planned and executed correctly because how optimal even also their execution of mining, if processing process / purification making that dig materials not saleable sold, for or less optimal and effective, hence earnings of result activity of mine as a whole also become less optimal. For that, regarding process to get the creation and maximizing of it make-up of maximal added value is the intention of government and company (Suyartono, 2003).

2.1.1.8. Metallurgy Study

Metallurgy test-drive require to be conducted in order to know how to extract metal from ore, which have been processed before, including the equipments and the corrected chemical reagent. For these mentioned hence factor the needed is to know the nature of ore cover specific gravity, hardness, item measure, and others (Suyartono, 2003).

2.1.1.9. Bulk Sampling

According to Suyartono (2003) there are some matters, which must be paid attention in estimation of bulk sampling definitively to know the quality. For example that is the determination of location of bulk sampling, result of exploration, which have been conducted before all and re- exploration.


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2.1.2. Mining Environment Protection

Mining activity obliged to look after environment adhered environment values. State government has arranged this study in “UU No. 23/1997” concerning Environment where each of gift permission of the mining effort have obligation to look after environment around mine site. This matter has an important impact where have to provide with environment impact assessment (AMDAL). Pursuant to the regulation by Department of Energy and Mineral Resource in “Kepmen Pertambangan dan Energi No. 1211.K/008/M.PE/1995” and other related / relevant regulation, obligation of conservancy of environment in mine site and its surroundings have to fulfill by company since the starting of exploration activity.

Considering the level of impact by mine activity, it needed some of management efforts, which is being planned and measured. Management of environment in mining sector usually embraces some principle of Best Management Practice. USEPA (1995) recommended some efforts that feasible to be used as an effort operation of mining impact activity to water resource, wild animal and vegetation (Suyartono, 2003).

Furthermore, Suyartono (2003) explains some efforts operation of environment handling for instance by using sediment structure protection, developing plan of waste operation system, avoiding activity of construction during critical farm, avoiding poisoned of cyanide, minimally usage of constrictor or fence to animal migration path, and prohibition over hunting wild animal in mine site.


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2.1.3. Mining Standardization

Formulation activity of Indonesian National Standard (SNI) of public mining until year 2002 have yielded Public Mining Standard (SPU) counted to 175 standards, which have been ratified by National Standardization Institute (BSN) become SNI. In the implementation, standard formulation activities are cooperation among all stakeholders, that is Department of Energy and Mineral Resource, Relevant Institution and Local Government as governmental proxy with standardization society (mine entrepreneur, mine consumer, college and institution) (Suyartono, 2003).

The formulation process then continue overspread elementary concept which have been discussed to mining standard user society in order to get comments, then conducting the Consensus Forum and proposed to BSN to be specified become SNI through solute discussion in BSN Standard Formulating Commission. The final formulation process of SNI is gone into effect obligatorily or voluntary in public mining area (mineral and coal mining) passing Decree of Energy and Mineral Resource Minister (Suyartono, 2003).

Suyartono (2003) explains in supporting and applying program racing of standardization in local government, hence needed peripheral of transparent and well policy establishment so that can give positive impacts for growth of mining investment in Indonesia, especially within applying policy of SNI in mining area. Rising of the “Peraturan Pemerintah No. 102/2000” which immediately lifted become law and regulation, hence Department of Energy and Mineral Resource Cq. General Directorate of Geology and Mineral Resource continue to formulate


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new policy of standardization of mining area in harmony with policy of national standardization policy.

2.2. DECISION SUPORT SYSTEM

Decision Support System (DSS) is an interactive, flexible, and adaptable Computer-Based Information System (CBIS), specially developed for supporting the solution of a particular management problem for improved decision making (Turban, 1993). Decision making is a process of choosing among alternative courses of action for the purpose of achieving a goal or goals (Turban, 1993). A decision support system (DSS) is a computer-based system that helps the decision maker utilizes data and model to solve unstructured problems (Sprague and Carlson, 1982).

The concept of DSS is based on the seminal work by Simon and associates in 1950s and 1960s (Simon, 1960). The Spatial Decision Support System (SDSS) concept has evolved in parallel with DSS. SDSS is an interactive, computer-based system designed to support a user or group of users in achieving a higher effectiveness of decision making while solving a semi-structured spatial decision problem (Densham, 1989). The development of SDSS has been associated with the need to expand the Geographic Information System (GIS) capabilities for tackling complex, ill-defined, spatial decision problems (Densham, 1989).

Similar to DSS, SDSS is composed of several software components which are the Data Base Management System (DBMS) with containing the functions to manage the geographic data base, the Model Base Management System (MBMS) with containing the function to manage the model base and the Dialog Generation and Management System (DGMS) with managing the interface between the user


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interface with display and report forms and the rest of the system or Graphical User Interface (GUI).

The decision making process adopted to solve semi-structured spatial problems is often perceived as unsatisfactory by decision makers. Densham (1991) lists the distinguishing capabilities and functions of SDSS, which should be capable of providing mechanisms for the input of spatial data, allowing representation of the spatial relations and structures, including the analytical techniques of spatial and geographical analysis and providing output in a variety of spatial forms, including maps.

2.3. INFORMATION SYSTEMS

An information system is a group of components that interact to produce information. The minimal information system consists of people, procedures, and data (Kroenke, 1989). According to Kroenke (1989), a good information system consideration if characteristics of it have been fulfilled such pertinence, timelines, accuracy, reduced uncertainty, and element of surprise.

An information system is an organized combination of people, hardware, software, communications networks, and data resources that collects, transforms, and disseminates information in organization (O’Brien, 1999). The components of these information systems describe on Figure 2.3. There are five components of information systems such as data resources, hardware resources, software resources, network resources, and people resources.


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Figure 2.3. Information system components (O’B rien, 1999)

According to O’Brien (1999), people resources include end user (people who are use an information systems or the information it produces) and IS specialist (people who develop and operate information systems). Hardware resources include all physical devices and materials used in information processing. Software resources include all sets of information processing instructions. Data is more than the raw material of information and includes wide variety of data type, how the data be organized (database) and knowledge bases. Network resources emphasize that communication network are a fundamental resource component of all information systems and include communication media and network support (Mulyarto, 2003).

The conducting of this research considering on IS components, i.e. software resource, data resource, and network resource. Data resource is one of vital aspect that have to manage carefully consider to the quality and validity of it. Network resource concern to the security of networking include of data transfer


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security, communication firewall, etc. As Mulyarto (2003) state that software resource concept included the sets of operating instructions (programs), and the sets of information processing instructions needed by people (procedures). 2.4. SYSTEM DEVELOPMENT

The systems approach to problem solving uses a systems orientation to define problem and opportunities and develop solutions. When the systems approach to problem solving is applied to the development of information system solution, it is called information system development or application development (O’Brien, 1999). Furthermore these system development popular called with system development life cycle (SDLC) which is includes phases of system such system investigation, system analysis, system design, system implementation and maintenance (Figure 2.4).

Figure 2.4. System Development Life Cycle (O’Brien, 1999)

In many case, the traditional SDLC have to be modified because its limitation such as the SDLC approach is costly and time consuming, inflexible and discourage change, and ill-suited to decision making (Hoffer, 2002). One alternative approach that can be used is prototyping. O’Brien (1999) explains


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prototyping is the rapid development and testing of working model, or prototypes, of new application in an interactive. Prototyping is an interactive process that combines steps of the traditional systems development (Figure 2.5). The advantages of prototyping are users are involved in design and captures requirements in concrete form (Hoffer, 2002).

Figure 2.5. Prototyping development stages (O’Brien, 1999) 2.5. INTERNET

2.5.1. Internet Definition

The increasing population on the Internet, from on-line surfing to e-commerce to interactive chatting, has made the Internet an integral part of our society. The nearly ubiquitous access to the Internet and interactive content of the World Wide Web (WWW) have made them a powerful means for people to access, exchange, and process information. Many applications in journalism, sciences, publishing, and other fields have been changed by and adapted for use on the internet (Plewe, 1997). The Internet is a modern information relay system


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that connects hundreds of thousands of telecommunication networks and creates an “internetworking” framework.

2.5.2. Basic Component of Internet

According to Aronoff (1989), the main frame of internet is web services or distributed services. The term services here refers to component services; that is, components with certain functions can be downloaded and reassembled data, including data input, storage, retrieval, management, manipulation, analysis, and output.

According to Peng and Tsou (2003) there four major components of Internet such are the client, Web server with application server, and data server (Figure 2.6). The client servers as user interface for user interface for users to interact with the Internet Programs. The Web server receives client requests, serves static Web pages, and invokes application servers. The application server manages server transactions, securities, and load balance. The data server serves geospatial and non-spatial data and provides data access and management through a Structured Query Language (SQL).

Figure 2.6. Basic components in Internet (Peng and Tsou, 2003)


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According to Peng and Tsou (2003) the client is a place for users to interact with objects and analysis functions in Internet. It is also a place for Internet uses graphic user interface to construct the client, Internet usually relies on the Web and Web add-ons as its client. A typical Web interface with HTML and forms is a simple client of Internet. But this simple HTML-based client has very limited user interactively. .

Furthermore, Peng and Tsou (2003) state that alternative clients who used Web add-ons have been developed to increase user interactively and helps users to interact directly with objects. There also include dynamic HTML and client-side applications such as plug-ins or help programs, Java applets or Java beans, and ActiveX controls. Dynamic HTML uses client-side scripting like JavaScript or VBScript to make the plain HTML dynamic.

2.5.2.2. Web Server

The second component in Internet is comprised of the Web server. The Web server is also called the HTTP server; its major function is to respond to requests from Web browsers via HTTP. There are several ways for the Web server to respond to client requests: (1) by sending existing HTML document or ready-made map images to the client, (2) by sending Java applets or ActiveX controls to the Web client, and (3) by passing requests to other programs and invoking other programs such as CGI that cloud process the queries (Peng and Tsou, 2003).

2.5.2.3. Application Server

When the Web server passes client requests to other programs, it requests services from application servers. An application server can be a glue program or


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middleware that connects the Web server and server-side applications such as a map server. An application server acts as a translator or connector between the Web server and the map server. The major functions of an application server include establishing, maintaining, and terminating the connection between the Web server and the map server; interpreting client requests and passing them to the map server, managing the concurrent requests and balancing loads among map server and data server; and managing the state, transaction, and security (Peng and Tsou, 2003).

2.5.2.4. Data Server

A data server serves data, in a relational or non-relational database structure. A client application such as a Web client or a map server gains access to the database through the SQL. Therefore, a database server is often referred to as a SQL server. Although SQL is an international standard language, the implementation by different vendors results in different versions of SQL for different database. Therefore, database middleware is often used to access different databases. There are three major database middleware: ODBC, Java Database Connectivity (JDBC), and Object Linking and Embedding Database (OLE DB) ActiveX Data Object (ADO), Through SQL, ODBC, or JDBC drive, the client application can query, retrieve, and even modify database records in the database server (Peng and Tsou, 2003).


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III.

RESEARCH METHODOLOGY

3.1. TIME AND LOCATION OF STUDY

This research was conducted from April 2005 to August 2005 and it took place in MIT Research Laboratory, SEAMEO-BIOTROP, Bogor; and Directorate of Mineral and Coal Engineering, Directorate General Geology and Mineral Resources, Department of Energy and Mineral Resources, Jakarta. The interest area of research covers several public mining companies in Indonesia (Figure 3.1) as data samples such PT. Tambang Batubara Bukit Asam (Coal Mining) in West Sumatera, PT. Aneka Tambang in West Java Province (Pongkor Project) and PT. Newmont Nusa Tenggara in West Nusa Tenggara Province (Batu Hijau Project).

Figure 3.1. Interest area of research 3.2. TYPE OF DATA AND SOURCES

Considering good mining practice, there several parameters that are used to evaluate mining activities performance such described in literature review (Chapter 2). Parameters which contain variable can be classified into quantitative


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parameters and qualitative parameters. Quantitative parameter is a parameter that can be accounted in particular unit and qualitative parameter is a kind of descriptive data which cannot account directly and needs a conversion method before.

This research only includes quantitative parameters which are environment monitoring parameter and mining engineering parameter. All these data is measured in each three months or quarterly (Triwulan) period which have been

submitted to department of energy and mineral resources in manually report. Thereby, all data are requirement analysis is based on these things such:

Environment monitoring data report is acquired from Directorate of

Environmental Geology and Mining Area and Mining Engineering data report is acquired from Directorate of Mineral and Coal Engineering. These two Directorates are under Directorate General Geology and Mineral Resources.

Spatial data of province in which mining company is operating and

specific mining area activity, which consist of administration boundary and river. This spatial data is acquired from National Survey and Mapping Agency (BAKOSURTANAL) and Department of Energy and Mineral Resources.

3.3. METHODS

3.3.1. System Development Method

Building a system development of this research refers to system development life cycle (SDLC) where it will divide into three phases of system


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development (see Figure 3.2) such investigation and analysis stage, design and implementation stage, and maintenance stage.

Figure 3.2. Research scheme

There are several steps included in investigation and analysis stage such current system and problem identification, user need analysis, component analysis and proposed system analysis. Study of current system is quite important to investigate advantages and disadvantages of the manual system (see Figure 3.3) and identify problems that occur as long as the system existed. Then, user need analysis is how to identify which users are going to be involved as stakeholder and the needs of users are also identified. Thus, component analysis is a step of identification of system components which is being used such parameter identification, hardware identification and software identification. Proposed system analysis is a step where a new system scheme is proposed.

According to the proposed system analysis, the next stage is design and implementation. It has three steps such database design, information system design and web based DSS design. In this stage, new proposed system is going to be design and construct begin with relational data, data connectivity, DSS analysis, physical design of information system and coding of web design. The


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last stage of this research scheme is maintenance stage which is testing of new prototype system.

Figure 3.3. Current system of evaluating mining company performance According to Figure 3.3, we can see that the evaluation of mining company performance is carried out partially, where there is no relationship among the quantitative components evaluation (mining environment and mining engineering) and those manual report are evaluated separately. Mining reports submitted directly in hardcopy type to the government which representative by

Department of Mineral and Energy Resources through its directorates of mineral engineering and environment.

Moreover, the report’s format has not been standardized yet whic h means the regulation of reporting is strongly depend on the characteristic of particular area of interest and its local regulation. Those reports is never been released to public or event local society and the current system is not involving stakeholder in mining performance evaluation.


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As there are some disadvantages of the current system, thus the system for evaluating mining company needs to be developed. The proposed system will cover problems found in the current existed system (Figure 3.4).

Figure 3.4. Proposed system for evaluating mining company performance 3.3.2. User Need Analysis

User need analysis is an important aspect to determine the users and their needs in a new proposed system. As a stakeholder of mining performance monitoring, user involvement has been identified into 2 (three) types, which are:

Actor

Actor here is mining company, who has access and responsibility for data input which is submitted online. Mining company is one of user that can store data to database server and the other users can monitor and evaluate of mining company performance.


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The evaluator of this MICES-Quan consists of Department of Energy and Mineral Resources (DESDM) and the observer and/or evaluator (institution / academic community, research institution, and mining expertise association, NGO). The evaluator can monitor periodical reports of mining company and giving mark of final evaluation regarding to their performance.

3.3.3. Component Identification 3.3.3.1. Parameter Identification

One thing of the importance section in this system is variable identification of the quantitative parameters. It has been impossible to conduct this job without determine the requirement of those, firstly. The requirement analysis of the mining quantitative parameters has been declared in national regulation. The large amount of source of parameter requirement come from study of document and mining report regarding mining company performance and small amount gathered from informal interview with mining and environment experts.

Several document such national regulations try to be included in this research suppose that parameters will perform in proportional way.

Act of the Republic of Indonesia Number 11 in the Year of 1967

concerning Mining Fundamental Rules

Act of the Republic of Indonesia Number 23 in the Year of 1997

concerning Environmental Management

♣ Government Regulation of the Republic of Indonesia Number 27 in the


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Government Regulation of the Republic of Indonesia Number 82 in the

Year 2001 regarding Water Quality Management and Pollution Water Protection

Government Regulation of the Republic of Indonesia Number 41 in the

Year 1999 regarding Air Pollution Control

Decree of the Minister State of the Environment Number 17 of the Year

2001 regarding The Types of Businesses and or Activities that must be Equipped With Analysis of the Businesses and or Activities Impacts on the Environment

♣ Decree of the State Minister for the Environment Number

KEP-51/MENLH/10/1995 regarding Liquid Waste Standard for Industrial Activities

♣ Decree of the State Minister for the Environment Number

KEP-45/MENLH/10/1997 regarding Air Pollution Standard Index

Quantitative components of good mining practice used for evaluating the performance as described before are mining environment and mining engineering. Each component has variables and some variables have sub-variables such: 1. MINING ENGINEERING

Mining engineering is one of quantitative parameter that have to measure in case of mining performance evaluation.

a. Reserve Addition

The additional mine material (raw material) that produced from proven reserve based on all factors of feasibility study fulfilled.


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b. Mining Operation

Mining operation means total area that can be opened for extracting ore material and waste rock and also volume of material produced from ore or called run off mine (ROM).

c. Production and Processing

There have several aspects in production and processing that have to consider such as synchronization of run off mine, processing and total content of mineral.

d. Stockpile

Stockpile regard to stock of ore material which will produce mineral, consist of low level ore and high level ore.

e. Shipping

Shipping will determine the capacity of ship vehicle in volume of composite material.

2. ENVIRONMENT MONITORING

Environment is also one of critical point in mining activity that has been directly infected to environment sustainability and local community

livelihood and indirectly infected to mining company performance. Monitoring of environment around mining area involves the calculation

and evaluation of physical and chemical condition of air quality, water quality and soil quality.

a. Cutting

Cutting determines vegetation area extraction that will use for extracting raw material.


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b. Cover Soil Peeling

Cover soil peeling is the next step after cutting which extract the top of soil surface. It consists of peeling for mined new area and hoarding for mined out area.

c. Sprout Soil Peeling

Sprout soil peeling is the next step after cover soil peeling which extract the next level of soil surface. It consists of peeling for mined new area and hoarding for mined out area

d. Mining Environment

Mining environment determine mine work area which consist of the active, mined out and tailing area.

e. Washing dan Purifying

Washing determines kind of chemical and water for washing and purifying determines tailing volume and processing.

f. Reclamation

Reclamation determines the recovery of mined out area, consist of soil hoarding and regevetation.

g. Air Quality Monitoring

Consist of aspects like sulfur oxide, nitrogen dioxide, etc. h. Water Quality Monitoring

Consist of physical and chemical aspect. i. Environment Cost (Rp)


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Following the list of capturing data based on parameter identification which consists of general mining company information (Table 3.1).

Table 3.1. General company information

No List of Information Stuffing Sample

1 Company Name Newmont Nusatenggara

2 Company Address (center office) Jakarta

3 Company Address (site office) Benete, Sumbawa Barat

4 Licence Type Kontrak Karya – KK

5 Licence Aggrement SK. ………

6 Licence Expired Period 2010

7 Licence Phase Exploration / Exploitation

8 Digging Materials Aurum, Cuprum, Nickel

9 Location Region ………

10 Area 35,000 Ha

11 Target Evaluation Percentage of Exploitation 12 Material Evaluation (Quarterly) IV, Year 2005

13 Mine Working System Open Pit

14 Mine Method Back Filling

3.3.3.2. Required Tools

Some supporting hardware and software will be employed to accomplish this research.

Hardware: PC Pentium IV class with minimum 2.4 GHz and 256 MB

RAM with operating system Windows 2000. This hardware is the minimum requirement for testing of system loading, working, and maintenance.

ESRI Arc View 3.2

This software needed for spatial data processing regarding Indonesia administration boundary, mining company activity boundary, etc.


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This is a programming language that used as engine for application server and developing information system.

MySQL 1.3

This is database application software which is freeware. It used to stored and retrieve all related data. The limitation of this software

capability describes on Table 3.2. Table 3.2. MySQL 1.3 limitation Operating System File-size Limit Linux 2.2-Intel 32 bit 2 GB (LFS:4 GB)

Linux 2.4 (Using ext3 file system) 4 TB

Solaris 9/10 16 TB

NetWare w/NSS file system 8 TB

Win32 w/FAT/FAT32 2 GB/4 GB

Win32 w/NTFS 2 TB (possible larger)

MacOS X w/HFS+ 2 TB

Apache Version 1.3.23

This is server software and also categorized as freeware which is used to connect database application (MySQL) and application server (Ms

Visual Basic).

Macromedia Dream Weaver MX 2004

This software is used for PHP script constructing and web design.

MapServer

This open source software is used to release spatial data in form of map to the web. MapScript in this software is used integrated with

PHP script.


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This is an ActiveX components from ESRI used in Microsoft Visual Basic 6.0 for map application programming.

3.3.4. Decision Support System Analysis

Decision Support System (DSS) analysis is important approach for performing variable evaluation especially quantitative parameters of mining company. Here, the scheme of DSS approach (see Figure 3.5) consists of parameters and variable evaluation. Quantitative parameter of good mining practice especially environment monitoring has been standardized using environment standard value model (Baku Mutu Lingkungan / BML). It has been publishing through legal aspect (Act of the Republic of Indonesia, Government Regulation, and Decree of the Minister). Those values are modeled based on specific characteristic requirement of location, soil condition, weather, etc.


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After defining variable or parameter identification, the next step is define the weighting of parameters and variable and scoring sub variable. For this purposes, the analysis form experts is required to define the range of its value whether good, fair or poor. All standard values have been simulated before and the final range is taken from average range of all the experts marking. Experts are chosen randomly based on their environment expertise and mining expertise. All these scoring value of sub variable will multiply with the weighting of parameters and variable to define the range of final performance.

3.3.4.1. Prospective Analysis

Brougeois (2002) in Sardjadidjaja (2005) explained the idea of prosprective analysis is to prepare several strategic action plans and show the changes is required in the future. The information about influence between factors is regarded from respondent’s interview. Respondent has been choose from mining expert and the environment experts such Government (Directorate of Mineral and Coal Engineering and Environment Ministry), private environment consulting

Respondents try to identify variable which is influenced to the topic and then analysis of relative dependence from one variable to the others with a scale 0 (means that not dependence), scale 1 (low dependence), scale 2 (adequate dependence), and 3 (high dependence).

The result of computerized influence / dependence matrix will show in quadrant level of dependence (Figure 3.6). Quadrant I is the key variable (input), quadrant II is connector variable (stakes), quadrant III is autonomous variable (unused) and quadrant IV is tied variable (output).


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Figure 3.6. Illustration of influenced factors in quadrant (modified from Sardjadidjaja, 2005)

3.3.4.2. Weighting and Scoring

Score evaluation is part of evaluation system which quantitative parameters include their variables try to be performed using weighting and scoring. Weighting of each variable is regard from their position in interest quadrant (Q) and the value (V) of quadrant (shown Figure 3.6). Scoring can be signed by performance value with scale 3 (adequate), scale 2 (intermediate) and scale 1 (inadequate). Total value of each variable will be categorized into the rank of evaluation.

Formula for weighting follow:

• Value in Q1 (A) = V1 X • Variable in Q1

• Value in Q2 (B) = V2 X • Variable in Q2

• Value in Q3 (C) = V3 X • Variable in Q3

• Value in Q4 (D) = V3 X • Variable in Q4 Total Value (TV) = A + B + C + D


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Weight in Q1 (WQ1) = A / TV Weight in Q2 (WQ2) = B / TV Weight in Q3 (WQ3) = C / TV Weight in Q4 (WQ4) = D / TV

Weight for each Variable Q1 (WvQ1) = (WQ1 / • Variable in Q1) X 100% Weight for each Variable Q2 (WvQ2) = (WQ2 / • Variable in Q2) X 100% Weight for each Variable Q3 (WvQ3) = (WQ3 / • Variable in Q3) X 100% Weight for each Variable Q4 (WvQ4) = (WQ4 / • Variable in Q4) X 100%

Formula for scoring follow: Score of Intensity Scale: 3 (Adequate) 2 (Intermediate) 1 (Inadequate)

Weighted Maximum Score:WcQ x Score of Intensity Scale Total Score = • Weighted Maximum Score

Rank of Evaluation Score: > 2.56 (Very Good) 2.16 – 2.55 (Good) 1.49 – 2.15 (Adequate) 0.95 – 1.48 (Bad) < 0.95 (Worst) 3.3.5. System Design

The architecture of new system design (Figure 3.7) of mining performance evaluation consists of four tiers which is web client (tier 1), web server (tier 2),


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application server (tier 3) and DBMS server (tier 4). Web client is web browsers with user interface where the users can interact with data and information. While, web server, server application and DBMS server is located in server and maintained by administrator. Web server and web client is connected through internet using transmission control protocol (TCP) or internet protocol (IP). Web server will design using dynamic hypertext markup language (DHTML) and personal home page hypertext preprocessor (PHP) where database can be visualized in web browser.

Figure 3.7. Architecture of system design

Consider to each tiers of system design, there are also a communication system to process the need of users (see Figure 3.8). Users can request data and information to web server and web server will invoke data from application server and connected to DBMS server. After retrieve data, application server will process data and sending the result to web server, and data result will deliver to web client. More detail of web communication process describes on event identification process (see Figure 3.9).


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Figure 3.8. Architecture of web communication process

Figure 3.9. Web event identification process


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IV.

RESULT AND DISCUSSION

This chapter is discussed about generating MICES-Quan system for evaluating mining company performance. This chapter consists of three major phases which are analysis of database design, analysis of system evaluation and the implementation in database, information system and web visualization. 4.1. ANALYSIS OF DATABASE DESIGN

4.1.1. Database Design

Database design describes about how data connect to other in term of the user, the needs, and the relationship. MICES-Quan database design explained with process modeling, conceptual model, logical model, and physical model. The methodology of database design explain the structure approach that uses procedures, techniques, tools and documentation aids to support and facilitate of design.

A design methodology consists of phases each containing a number of steps, which guide the designer in the techniques appropriate at each stage of the project. A design methodology also helps the designer to plan, manage, control, and evaluate database development projects. It is a structured approach for analyzing and modeling a set of requirements for a database in a standardized and organized manner (Connolly and Begg, 2002).

a. Process Modeling

Process modeling explains about interconnecting between data input, processes and data stores which is visualizing with data Flow Diagram (DFD). DFD describes user identification and the needs in the system visualization with context diagram (Figure 4.1). DFD also can be figured out in several


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levels of connection and relationship (Figure 4.2). Context Diagram figures out the user with their need to the system. There are three major users that will include to MICES-Quan system which are energy and mineral resources (DTMB), mining company, and public.

Figure 4.1 MICES-Quan Context Diagram

Directorate of Mineral and Coal Engineering (DTMB), Directorate

General Geology and Mineral Resources, Department of Energy and Mineral Resources, as government representative who can evaluate the performance of mining company.

Mining Company as the actor of the system which can submit their

periodical report digitally through internet yet manual report submitted.

♣ Public which consists of academician, researcher, mining association,

environment association, NGOs, and local community. They can be an observer only to browse the information and also can be an evaluator depends on their capabilities.


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Figure 4.2. MICES-Quan DFD Level 1 b. Conceptual Model

Conceptual model explain the concept of database which is the process of constructing a model of the information used in an enterprise. According to Connolly and Begg (2002) explained the conceptual design phase begins with the creation of a conceptual data model of the enterprise, which is entirely independent of implementation details such as the target of DBMS, application program, programming languages, hardware platform, performance issues, or any other physical consideration.

A Conceptual model describes the essential semantics of system data. A conceptual model consists of a number of symbols joined up according to certain conventions. Commonly, conceptual modeling use symbols from a


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modeling method known as entity-relationship analysis. This method was first

introduced by Chen in 1976 and now is widely used (Hawryszkiewycz, 1994). Conceptual modeling deals with the question on how to describe in a declarative and reusable way the domain information of an application, its relevant vocabulary, and how to constrain the use the data, by understanding what can be drawn from it. The entity relational of MICES-Quan system illustrated in Figure 4.3.

The analysis of ER describes three main part such:

Entities, object that have independent physical or conceptual existence. ♣ Relationship, which are meaningful interactions between the entities,

Attributes, which are the properties of the entities and relationship.


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c. Logical Model

Logical model explain the logic of database which is the process of constructing a model of information used in an enterprise based on specific data model, but independent of a particular DBMS and other physical consideration.

The logical model describes structure database in a particular Data Description Language (DDL). According to Shekhar et al (1999), logical

modeling phase is related to the actual implementation of the conceptual data model in database management system. Logical model identifies the requirement of data. The logical model of MICES-Quan showed Table 4.1. Table 4.1. MICES-Quan logical data model

No Category Entity Attribute

reserve_addition Company_id, Year, Quarterly, oreamount_unit, oreamount_plan, oreamount_real

production_processing Company_id, Year, Quarterly, minedromore_unit, minedromore_plan, minedromore_real

Mining_operation Company_id, Year, Quarterly, openedarea_unit, openedarea_plan, openedarea_real

1 Mining Engineering

stockpile Company_id, Year, Quarterly, lowlevelorestock_unit, lowlevelorestock_plan, lowlevelorestock_real air_quality Company_id, Year, Quarterly,

sulfuroxide _unit, sulfuroxide _plan, sulfuroxide _real

water_quality Company_id, Year, Quarterly, arsen_unit, arsen_plan, arsen_real cutting Company_id, Year, Quarterly,

cuttingarea_unit, cuttingarea_plan, cuttingarea_real

2 Environment Mining Monitoring

reclamation Company_id, Year, Quarterly, reclamationarea_unit, reclamationarea_plan, reclamationarea_real Standard_airquality sulfuroxide_standard,

nitrogendioxide_standard 3 Standard

Standard_waterquality merqury_standard, arsen_standard, chloride_standard


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No Category Entity Attribute

Company Company_id, Company_name, Company_Field, Location, Username, Password

User User_id, User_group, User_name, Password

4 Other

User_Group Number, User_group

d. Physical Model

Physical model describe the physic of database visualization. The physical design allows the designer to make decisions on how the database is to be implemented. Therefore, physical design in tailored a specific DBMS. There is feedback between physical and logical design, because decision taken during physical design for improving performance may affect the logical data model (Connolly and Begg, 2002).

Physical model describes the data physically where entity is set based on database software. MySQL as a database system is used; therefore all the attributes and data type will be set following the MySQL format.

Table 4.2. MICES-Quan physical design

No Table Column Type Width

1 reserve_addition Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

oreamount_unit Varchar 10 oreamount_plan Double 9 oreamount_real Double 9 2 production_processing Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

minedromore_unit Varchar 10 minedromore_plan Double 9 minedromore_real Double 9 4 mining_operation Company_id Varchar 15

Year Varchar 5


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No Table Column Type Width openedarea_unit Varchar 10 openedarea_plan Double 9 openedarea_real Double 9

5 stockpile Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

lowlevelorestock_unit Varchar 10 lowlevelorestock_plan Double 9 lowlevelorestock_real Double 9

6 air_quality Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

sulfuroxide_unit Varchar 10 sulfuroxide_plan Double 9 sulfuroxide_real Double 9

7 water_quality Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

arsen_unit Varchar 10

arsen_plan Double 9

arsen_real Double 9

8 cutting Company_id Varchar 15

Year Varchar 5

Quarterly Integer 2

cuttingarea _unit Varchar 10 cuttingarea _plan Double 9 cuttingarea _real Double 9 9 standard_airquality sulfuroxide_standard Double 10

nitrogendioxide_stand ard

Double 10

10 standard_waterquality merqury_standard Double 10 arsen_standard Double 10 chloride_standard Double 10

11 Company Company_id Varchar 15

Company_name Varchar 50 Company_Field Varchar 30

Location Varchar 20

Username Varchar 15

Password Varchar 15

12 User User_id Varchar 15

User_group Varchar 20

User_name Varchar 20

Password Varchar 10

13 User_Group Number Integer 10


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4.1.2. User Interface Design

Beside web development, MICES-Quan also requires information system development. It will put on server as center of calculation process. Developing of the information system application requires Microsoft Visual Basic 6.0 for user interface design. According to Flemming (1998) in Mulyarto (2003), there are seven basic principles in designing user interface includes; user in control, consistency, forgiveness, feedback, aesthetics, and simplicity.

User in Control. An important principle of user interface design is that the user should always feel in control of the software rather than feeling controlled by the software.

Consistency. Consistency allows user to transfer existing knowledge to new tasks, learn new things more quickly, and focus more attention on tasks. This is because they do not have to spend time to trying to remember the differences in interaction. By providing a sense of stability, consistency makes the interface familiar and predictable.

Forgiveness. Users like to explore an interface and often learn by trial and error. An effective interface allows for interactive discovery. It provides only sets of choices and warns users about potential situations where they could damage the system or data, or better, makes actions reversible or recoverable.

Aesthetics. Visual design is important part of an applications interface. Visual attributes provide valuable impressions and communicate important cues to the interactive behavior of


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particular objects. At the same time, it is important to remember that every visual element that appears on the screen potentially competes for the user’s attention.

Simplicity. An interface should be simple (not simplistic), easy to learn, and easy to use. It most also provide access to all functionality of an application. Maximizing functionality and maintaining simplicity work against each other in the interface.

4.1.3. Web Design

Web design is one way to communicate user and their needs. The material of communicate through information such graphic, tabular, image, text, multimedia. According to Lynch and Horton (2002) in Mulyarto (2003), there are several advises that should be considered in designing web pages, such as visual hierarchy, consistency and page dimensions.

Visual Hierarchy. The primary task of page design is to create a strong, consistent, visual hierarchy in which important elements are emphasized and content is organized logically and predictably. Figure 4.4 shows the information hierarchy of MICES-Qual web pages


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parameter directly with selecting mining company and year of production

- Can zoom the location of mining company


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- Can monitor the evaluation of mining company in particular period simultaneously


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- Can browse information along with browser / observer - Register with Log In

- Fill report online for each variables of quantitative parameters


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- Log out to finish registration of report


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- Can browse information along with browser / observer - Register with Log In

- Fill evaluation form


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