Web based decision support system for monitoring coral reef management (Case study of Liukang Tupabbiring Sub District, Pangkajene Kepulauan District)

WEB BASED DECISION SUPPORT SYSTEM FOR
MONITORING CORAL REEF MANAGEMENT
(Case Study of Liukang Tupabbiring Sub District, Pangkajene Kepulauan District)

AHMAD MAULIDDIN

GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2011

STATEMENT

I am Ahmad Mauliddin stated that this thesis emitted:
Web Based Decision Support System for
Monitoring Coral Reef Management
(Case Study of Liukang Tupabbiring Sub District, Pangkajene Kepulauan District)
Is the result of my own works during the period of March 2011 to September
2011 and it has not been published before. The contents of the thesis have been
examined by the advisory committee and an external examiner.

Bogor, September 2011

Ahmad Mauliddin
G051070011

ABSTRACT
Scientific study result is the primary information on coral reef condition and
a decision-making management tool. Performance evaluation of coral reef
management needs to be based on an update (actual) and open access information
in order to help decision maker to provide appropriate programs. Management of
coral reef is implemented with several evaluation criteria formulated with
parameters and variables in management activity aspects. DSS is one of the tools
and methods for management decision. In conjunction with the coastal space, the
tools can use Spatial Decision Support System (SDSS) as a comprehensive
decision support integrated with Geographical Information System (GIS). This
SDSS provided effective decision making process that can handle spatial and non
spatial database. Using the internet will make it easier for all components in coral
reef management in monitoring the condition of coral reefs. Within decision
support system, all variables in coral reef management will be managed through
data processing methods to produce several recommendations that perform and

help decision maker to find the state of management performance. The objective
of the research are; to develop database system for inventorying coral reef and
socio-economic aspect; to develop a web GIS that can be used by decision makers
to identify the state of reef management through the internet access; to develop
prototype decision support system tool called Coral Reef Management Evaluation
System (CRES). A prototype of database system has been developed to be able to
visualize monitoring of coral reef data. Prototype of Web GIS has been
implemented to utilize coral reef management become important input for
decision maker for monitoring coral reef. Prototype of the DSS tool is capable to
provide recommendation for monitoring coral reef management.

Keywords: Web GIS, Decision Support System, Database, Coral Reef Monitoring,
Management, CRES

ABSTRAK
Hasil studi ilmiah adalah informasi utama dalam mengetahui kondisi
terumbu karang dan alat pengambilan keputusan. Evaluasi kinerja pengelolaan
terumbu karang perlu didasarkan pada pembaruan data dan akses informasi
terbuka dalam rangka membantu pengambil keputusan untuk melaksanakan
program yang sesuai. Pengelolaan terumbu karang diimplementasikan dengan

beberapa kriteria evaluasi yang dirumuskan dengan parameter dan variabel dalam
kegiatan pengelolaan. DSS adalah salah satu alat dan metode untuk pengambilan
keputusan pengelolaan. Dalam hubungannya dengan ruang pesisir, dapat
menggunakan Spatial Decision Support System (SDSS) sebagai pendukung
keputusan komprehensif yang terintegrasi dengan Sistem Informasi Geografis
(GIS). SDSS dapat menyediakan proses pengambilan keputusan yang efektif yang
dapat menangani database spasial dan non spasial. Menggunakan internet akan
memudahkan semua komponen dalam pengelolaan terumbu karang dalam rangka
memantau kondisi terumbu karang. Dalam sistem pendukung keputusan, semua
variabel dalam pengelolaan terumbu karang akan dikelola melalui metode
pengolahan data untuk menghasilkan beberapa rekomendasi yang membantu
pengambil keputusan setelah menemukan kinerja manajemen. Tujuan dari
penelitian ini adalah, untuk mengembangkan sistem database untuk inventarisasi
kondisi terumbu karang dan aspek sosial-ekonomi, untuk mengembangkan web
GIS yang dapat digunakan oleh pengambil keputusan untuk mengidentifikasi
keadaan pengelolaan terumbu karang melalui akses internet, untuk
mengembangkan prototipe alat dukungan keputusan disebut Sistem Evaluasi
Manajemen Terumbu Karang (CRES). Sebuah prototipe dari sistem database telah
dikembangkan untuk dapat memvisualisasikan data pemantauan terumbu karang.
Prototipe GIS Web telah diterapkan untuk memanfaatkan pengelolaan terumbu

karang menjadi masukan penting bagi pengambil keputusan untuk memantau
terumbu karang. Prototipe alat DSS adalah mampu menyediakan rekomendasi
untuk manajemen pemantauan terumbu karang.
Kata kunci: Web GIS, Decision Support System, Database, Pemantauan Terumbu
Karang, Manajemen, CRES

SUMMARY
AHMAD MAULIDDIN (2011). Web-Based Decision Support System for
Monitoring Coral Reef Managementn (Case Study: Liukang Tupabbiring
Sub District, Pangkajene Kepulauan District). Under supervision of Setyo
Pertiwi and Neviaty P. Zamani.
Coral reefs are composed from various connected habitats which live
together in the surface of ocean bottom to water column. Scientific monitoring is
the primary source of information on coral reef condition and a decision-making
management tool.
Management of coral reef is implemented with several evaluation criteria
formulated with parameters and variables in management activity aspects.
Performance evaluation of coral reef management needs to be based on update
(actual) and open access information in order to help decision maker to provide
appropriate programs. Within decision support system, all variables in coral reef

management will be managed through data processing methods to produce several
recommendations that perform and help decision maker to find the state of
management performance.
Management of coastal area is the complex problem. Policy makers need
tools that can integrate coastal area resources data, so that appropriate decisions
based on the data can be made. One of the tools and methods used is DSS. In
conjunction with the coastal space, the tools can use Spatial Decision Support
System (SDSS) as a comprehensive decision support integrated with
Geographical Information System (GIS). This SDSS provided effective decision
that can handle spatial and non spatial database. The system allows the spatial and
non spatial dataset organization, analysis and transformation for obtaining the
required information.
The objective of the research are; to develop database system for
inventorying ecological and socioeconomics aspect; to develop a web GIS that
can be used by decision makers to identify the state of reef management through
the internet access; to develop prototype decision support system tool called Coral
Reef Management Evaluation System (CRES).
The criteria of coral reef management are coral reef condition, water quality
condition, environment condition, demography, livelihood, institutional, fishing
gear and coverage of coral reefs. These criteria based on literature and the

availability data. Scoring and weighting system was applied for assessing
performance of management. Decision of weighting value based on the
importance of factor for coral reef management. Value of weighting is give by
expert team which has capabilities and experience in coral reef management. DSS
tool analysis to be use in determining the level of state management is a multicriteria analysis with defined criteria and indicators. This tool will be built on
website based systems.
DSS is developed by prototyping method. This method simplifies and
accelerates the steps of system development life cycle (SDLC). The main idea is
using web GIS and decision support system to developed system information for
coral reefs management. SDLC approach is used to ensure the success of the
research. SDLC approach commonly called as system development life cycle

vi

involves several steps: (1) Analysis, (2) Design, (3) Construction/Implementation,
(4) Maintenance. All these phases are cascaded to each other so that the second
phase they will started and when set of goals defined are achieved for first phase
then they will be it is signed off.
The first step is to understand the requirements of developing DSS including
problem identification; user will need analysis, data collecting and data

preparation. Preliminary analysis was conducted to identify the problems of coral
reefs management. There are lot of research data about coral reefs condition. Data
presented mostly of in written report. There are difficulties in using these data for
the management process, especially in observing changes of the coral reefs
condition, so that appropriate programs will be hard to be chosen. The
requirement analysis involves district officer as the target users of DSS. Analysis
of user needs was carried out by direct interviews towards several parties
including district staff, academics and NGOs. The results of interviews will then
draft to a list of requirement by the stakeholders.
Spatial data such as topographical maps, satellite imagery and digitization of
maps are collected from several sources. A topographic map in digital format is
easier to manage because it has a standard, so can be instantly used. Maps derived
from satellite imagery and digitized maps hardcopy is necessary more steps to be
a spatial data such as topographic maps.
The main factor in determining coral reef condition is a percentage of life
coral as this also standard of rating the coral condition according to Ministry of
Environment Decree No. 4, Year 2001 on Standard Criteria of Coral State. Water
Quality data is according to Ministry of Environment Decree No. 51, Year 2004
on Standard Criteria of Water Quality for Marine Biota.
Estimation of seabed coverage is obtained from coverage classification of

Landsat satellite image by combining Band 321 to differentiate island/land with
coral reef area. In monitoring trend of coverage dynamic, time series analysis has
been conducted using Landsat image from year 2000, 2005, and 2010. Result
from this analysis is expected to give comparation of coral reef coverage in study
location from time to time as also compared with field measurement according
with collected data in the field. Image classification analyzed just focusing on
coral coverage only without considering the other substrate type of the sea bed.
Socio-economy data collected are quantitative data which referred to
average income of respondents working in the fishing and other sectors. These
data have been inputted into database to be compared with the initial data. Other
socio-economic factors that have become focus of attention are demography and
people density, occupation related with coral reef. Fishing catching tools and
quantity of fish catch are also used in analyzing the relation between coral and
catching tools used by the people.
Preparation of data was done after all the necessary data components have
been collected. They are managed in to the system database for later introduction
into the DSS. This database system is managed by using the software
PostGreSQL and PostGIS. For the satellite image data, after the bottom cover
classification process it is converted into vector data with a database connected to
the PostGreSQL.

vii

vii

A set of alternative strategies/recommendations was formulated which refers to
the effectivenes of previous programs on coral reef management. This will be the
output of the system after the evaluation process.
Web pages were created by coding it in a PHP programming language. PHP
is scripting language which is integrated into HTML page and run in server side.
PHP Script can be written by using notepad or special software design such as
PHP Expert Editor, Macromedia Dreamweaver MX 2004. All the PHP syntax we
coded in a page will be fully run in the server. What users see on the browser is
the result of the process in the server.
Testing was done by using one personal computer which will act as the
server and workstation. In order to access the web, Apache server should be
installed in the operating system. Testing results indicate that the system has
worked well as it is intended to perform.
As the result, a prototype of database system has been developed to be able
to visualize monitoring of coral reef data. Prototype of Web GIS has been

implemented to utilize coral reef management become important input for
decision maker for monitoring coral reef. Prototype of the DSS tool is capable to
provide recommendation for monitoring coral reef management.

vii

Copyright @2011, Bogor Agricultural University
Copyright are protected by law,
1. It is prohibited to cite all of part of this thesis without referring to and
mentioning the source:
a. Citation only permitted for the sake of education, research, scientific
writing, report writing, critical writing or reviewing scientific problem.
b. Citation does not inflict the name and honor of Bogor Agricultural
University.
2. It is prohibited to republish and reproduce all part of this thesis without written
permission from Bogor Agricultural University

WEB BASED DECISION SUPPORT SYSTEM FOR
MONITORING CORAL REEF MANAGEMENT
(Case Study of Liukang Tupabbiring Sub District, Pangkajene Kepulauan District)

AHMAD MAULIDDIN

A thesis submitted for the Degree of Master of Science in Information
Technology for Natural Resources Management Program Study

GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2011

External Examiner: Prof. Dr. Ir. Dedi Soedharma, DEA

Research Title

: Web Based Decision Support System for Monitoring
Coral Reef Management (Case Study of Liukang
Tupabbiring Sub District, Pangkajene Kepulauan District)

Student Name

: Ahmad Mauliddin

Student ID

: G051070011

Study Program

: Master of Science in Information Technology for Natural
Resources Management

Approved by,
Advisory Board

Dr. Ir. Setyo Pertiwi, M.Agr
Supervisor

Dr. Ir. Neviaty P. Zamani, M.Sc
Co-Supervisor

Endorsed by,

Program Coordinator,

Dean of the Graduate School

Dr. Ir. Hartrisari Hardjomidjojo, DEA

Dr. Ir. Dahrul Syah, M.Sc.Agr

Date of Examination:
September 26, 2011

Date of Graduation:

ACKNOWLEDGMENT
Firstly, I would like to express my gratitude to Allah SWT for the blessings and
mercies to me so far. I want to thank my supervisor Dr. Ir. Setyo Pertiwi, M. Agr
and my co-supervisor Dr. Ir. Neviaty P. Zamani, M. Sc for guidance, suggestions,
comments, encouragement and constructive criticism during my research
supervision through all the months until the study is completed.
I highly like to express my highest gratitude to beloved my parents Ibrahim Tahir
and Hj. St. Aisyah Mansur that their love is never end, assistance and moral
support has been tremendous brought me to this point. Also all to my brother and
sisters for their care and support
I also want to thank and give an appreciation to MIT Class 2007 for togetherness,
support, and enlightenment with all this, how we support each other during the
study until the last semester of our research. This is really a great gift and
privilege for me to find great people with different backgrounds and expertise as
you. I want to thank you also to Chairman Program Dr.Ir. Hartrisari
Hardjomidjojo, DEA and the staff of the Master of Science in Information
Technology for Natural Resource Management (MIT) for good cooperation and
facilities, special thanks also to the MIT Lecturers to share their knowledge and
experience.
A big thank you also goes to:
Staff Center for Coral Reef Research (CCRR) Hasanuddin University, special
thanks to Dr. Rijal Idrus, MSc, Ir. Dewi Yanuarita, MSc, and Nurliah Buhari,
S.Pi, MSi, for his help to the author that this thesis can be resolved.
2. Prof. Dr. Ir. Chair Rani, M.Si and Dr. Nurjannah Nurdin, M.Si for the advice
and constructive input to preparation of this thesis.
3. All my friends at Marine Conservation Foundation, and especially Andi
Muhammad Ibrahim, ST, M.Sc, Muh. Ikhsan A, ST, MT for all the
suggestions and discussion time.
1.

At last, to my beloved wife Armala Sary, SE. thank you for your support,
patience, attention, devotion, and everything during my studies.

CURRICULUM VITAE
Ahmad Mauliddin, born in Makassar, South Sulawesi,
Indonesia on March 25, 1975. He spent most of his childhood
and school from elementary to university in Makassar. He
achieved

a bachelor's degree

from the University of

Hasanuddin, Makassar in the Faculty of Marine Sciences. Since
2000 has been active in Marine Conservation Foundation in Makassar.
In 2011, Ahmad Mauliddin earned a master's at MIT (Master of Science in
Information Technology) for Natural Resources Management Program at the
Bogor Institute of Agriculture. He proposed a system for web-based decision
making for evaluating the management of coral reefs in the Liukang Tupabbiring
Sub District - Pangkajene Kepulauan District.

LIST OF CONTENTS

STATEMENT .......................................................................................................... i
ABSTRACT ........................................................................................................... iii
SUMMARY ............................................................................................................ v
ACKNOWLEDGMENT ....................................................................................... xv
CURRICULUM VITAE ..................................................................................... xvii
LIST OF CONTENTS ......................................................................................... xix
LIST OF FIGURE ................................................................................................ xxi
LIST OF TABLE ................................................................................................ xxii
LIST OF APPENDIX ........................................................................................ xxiii
I

INTRODUCTION ........................................................................................... 1
I.1
I.2
I.3

II

Background ..............................................................................................1
Scope of Research ...................................................................................2
Objective..................................................................................................2

LITERATURE REVIEW ................................................................................ 5
II.1 Web Geographic Information Systems (WebGIS) ..................................5
II.2 Decision Support System ........................................................................5
II.2.1 Multi-criteria Decision Analysis (MCDA) ..................................6
II.2.2 Ranking and Rating .....................................................................8
II.3 Database Management System ................................................................9
II.3.1 Storage .......................................................................................10
II.3.2 Retrieval .....................................................................................10
II.3.3 Control .......................................................................................10
II.4 Monitoring Coral reef ............................................................................11
II.4.1 Monitoring with Remote Sensing Data .....................................11
II.4.2 Socio-economic Condition ........................................................13
II.4.3 Coral Reef Condition .................................................................15
II.4.4 Decision Support to Monitoring Coral Reefs ............................16

III METHODOLOGY ........................................................................................ 19
III.1
III.2
III.3
III.4

Time and Location of the Research .......................................................19
Data and Research Materials .................................................................19
Hardware and Software .........................................................................19
Methods .................................................................................................21
III.4.1 Requirements Analysis ..............................................................21
III.4.2 System Design ...........................................................................24
III.5 Decision Model .....................................................................................26
III.6 Data Collection ......................................................................................30
III.6.1 Data of Coral Reef Condition ....................................................30
III.6.2 Data of Socio-economic Condition ...........................................32

xx

III.7 Limitation .............................................................................................. 33
IV RESULT AND DISCUSSION ...................................................................... 35
IV.1 General Information on Study Area ...................................................... 35
IV.2 Requirement Analysis ........................................................................... 36
IV.2.1 User Need Analysis ................................................................... 36
IV.2.2 The Data .................................................................................... 36
IV.2.3 Data Preparation ........................................................................ 38
IV.3 Decision Support System Design .......................................................... 39
IV.3.1 Process Modeling ...................................................................... 39
IV.3.2 Conceptual Modeling ................................................................ 40
IV.3.3 Logical Modeling ...................................................................... 41
IV.3.4 Physical Design ......................................................................... 41
IV.3.5 Databases ................................................................................... 42
IV.3.6 Analysis ..................................................................................... 42
IV.4 Construction .......................................................................................... 43
IV.4.1 Web Page Code Constructing ................................................... 43
IV.4.2 Testing ....................................................................................... 48
IV.5 Implementation ..................................................................................... 49
IV.6 System Advantage ................................................................................ 49
V

CONCLUSION AND RECOMMENDATION ............................................. 51
V.1 Conclusions ........................................................................................... 51
V.2 Recommendations ................................................................................. 51

REFERENCES ...................................................................................................... 53

xx

xxi

LIST OF FIGURE
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21

Figure application of MCA Techniques to the Selection and
Scoring of Criteria and Indicator (Mendoza, G. A., 1999) ...................9
Cross Section Through a Coral Reef Showing the Major Zones
(Jos Hill at al., 2004)...........................................................................13
The ICM Policy Cycle. (Ehler, 2003) ................................................ 16
Structure of the Coral Decision Support System (Ruitenbeek et
al., 2000) ............................................................................................ 18
Location of Spermonde Islands (DFW Indonesia, 2003) ................... 20
General Research Scheme .................................................................. 22
Framework of the Research................................................................ 23
System Proposed for Coral Reef Management .................................. 24
Design of system architecture of the Coral Reefs Evaluation
System (CRES) .................................................................................. 25
Structure of Decision Model for Coral Reef Management ................ 26
Context Diagram of the System ......................................................... 39
Data Flow Diagram of the System ..................................................... 40
Entity Relationship Diagram of the System ....................................... 41
Page uses PHP Script ......................................................................... 43
Display of Spatial Mapping and Zoom in Location of Study ............ 45
Form to Input a New Data of Coral Reef Condition .......................... 45
Add New Data Socio-economic ......................................................... 46
Coral Reef Comparison Area ............................................................. 46
Page of comparison coral reef area by villages .................................. 47
Page of Report of Coral Condition..................................................... 47
Page of Report Analysis of Total Score of Each Criteria .................. 48

xxi

xxii

LIST OF TABLE
Table 1
Table 2
Table 3
Table 4
Table 5
Table 6
Table 7

xxii

Regular Ranking Value......................................................................... 9
Matching Management Problems on Coral Reefs to the
Available Toolbox (Jos Hill, 2004). ................................................... 17
Category and Scoring for Each Variable ............................................ 27
Weighting of Evaluation Parameters by Experts ................................ 28
Range of Scores Indicating Performance of Coral Reef
Management ....................................................................................... 29
Matrix Recommendation Program for Coral Reef Management ....... 30
Table Logical Data Model .................................................................. 42

xxiii

LIST OF APPENDIX
Appendix 1
Appendix 2
Appendix 3
Appendix 4

Strategy and Action Plan for coral reef management .................... 57
Physical Design of the system ....................................................... 60
Database structure on PostgreSQL ................................................ 62
Weight analysis for determine status of coral reef
management and appropriate program recommendations
for sample site (village Mattiro Bombang) ....................................63

xxiii

I
I.1

INTRODUCTION

Background
The coral reefs are composed from various connected habitats which live

together in the surface of ocean bottom to water column. Scientific monitoring is
the primary source of information on coral reef condition and a decision-making
management tool (Tissot at al., 2002).
Management of coral reef is implemented with several evaluation criteria
formulated with parameters and variables in management activity aspects.
Performance evaluation of coral reef management needs to be based on update
(actual) and open access information in order to help decision maker to provide
appropriate programs. Within decision support system, all variables in coral reef
management will be managed through data processing methods to produce several
recommendations that perform and help decision maker to find the state of
management performance.
Management of coastal area is the complex problem. Policy makers need
tools that can integrate coastal area resources data, so that appropriate decisions
which based on valid data can be made. One tool and method used is DSS. In
conjunction with the coastal space, the tools can use Spatial Decision Support
System (SDSS) as a comprehensive decision support that integrated with
Geographical Information System (GIS). This SDSS provided effective decision
that can handle spatial and non spatial database. The system allows the spatial and
non spatial dataset organization, analysis and transformation for obtaining the
required information.
Generally, spatial decisions making has a meaning as “closed” process with
limited parameter input to get a better output. Nowadays some spatial decisions,
have been made by people as a planner who work for government with less real
specification, while it is claimed that the decision reflects public needs and also
claimed as public opinion (Malczewski, 1999).
As its function of providing data and information, some of GIS application
for certain purposes, are developed in web GIS. It means that the GIS are able to
be accessed via internet. Users that have particular interest about data and
information can access directly through web to get what they need.

2

Implementation of coral reefs management requires open access data,
because of the community as important part which directly involved in the
management of coral reefs. All stakeholders in coral reef management should
share data and information to build a good system in the management of coral
reef. The policy makers also require data sharing and information from all
stakeholders involved in coral reef management. Therefore the role of the internet
is important as the bridge between decision-makers with other stakeholders.
Internet became an option because of its easy and cheap.
I.2

Scope of Research
Management and conservation of coral reef ecosystems is a long-term

program that requires time to return or close to the initial condition. To achieve
the use of coral reef in Indonesia, there are two dominant aspects that must be
considered; those are coral reef condition and socio-economic condition.
Percentage of live coral cover is one of the important indicators in coral reef
management. Socio-economic conditions can also be a sign the sustainable for
management of coral reefs. Those two aspects are the basis of this research for
designing a tool for policy making. The tools are planned to be constructed by
using the internet media and they are expected to help decision makers at local
level. Also can use for monitoring and evaluation of performance management at
local/regional level.
The research sample area is sub district of Liukang Tupabbiring, Pangkajene
Kepulauan district, which will be focused on coral reef management area based on
the village level.
I.3

Objective
The objective of this research will be divided into three, those are:

1. To develop database system for inventorying Coral reef and socio-economic
aspects.
2. To develop a webGIS system that can be used by decision makers to identify
the state of reef management through the internet access.
3. To develop decision support system tool called Coral Reef Management
Evaluation System (CRES).

3

The expected output of this research is a Decision Support System (DSS)
tool that can be used by government to evaluate coral reef management condition
regarding Coral reef and socio-economic aspects.

4

II LITERATURE REVIEW
II.1 Web Geographic Information Systems (WebGIS)
A geographic information system (GIS) integrates hardware, software and
data for capturing, managing, and displaying all forms of geographically
referenced information. GIS allows us to view, understand, question, interpret,
and visualize data in many ways that reveal relationship, patterns, and trends in
the form of the maps, globes, reports and charts. A GIS helps you answer question
and solve problem by locking at your data in a way that is quickly understood and
easily shared (ESRI, 2000).
Much recent attention has focused on developing GIS functionality in the
internet, Worldwide Web, and private intranets and is sometimes termed in Web
GIS. Internet users will be able to access GIS applications from their browsers
without purchasing proprietary GIS software. Web GIS will make it possible to
add GIS functionality to a wide range of network-based application in business,
government, and education. The challenge of Web GIS lies in creating software
systems that are platform independent and run on open TCP/IP-based network,
that is on any computer capable of connecting to the internet (or any TCP/IPbased network) and running a web browser (Foote and Kirvan, 1997).
II.2 Decision Support 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.
Decision making is a process of choosing among alternative courses of action for
the purpose of achieving a goal or goals (Efraim 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 (Ralph H. Sprague at al.,
1982).
The Spatial Decision Support System (SDSS) concept has evolved in
parallel with DSS. SDSS is an interactive, computer-based system design to
support a user or group of users in achieving a higher effectiveness of decision
making while solving a semi-structured spatial decision problem. The

6

development of SDSS has been associated with the need to expand the
Geographic Information System (GIS) capabilities for tackling complex, illdefined, spatial decision problems (Densham at al., 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
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) list the distinguishing capabilities and function 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.
II.2.1 Multi-criteria Decision Analysis (MCDA)
MCDA is a discipline knowledge that aimed at supporting decision makers
who are faced with making numerous and conflicting criteria evaluations. MCDA
aims at highlighting these conflicts and deriving a way to come to a compromise
in a transparent process. MCDA help the decision makers in the territory
management, several actors have shown the adequacy of the association of the
geographical information systems (GIS) and the multi criteria decision aid
(MCDA) methods.
Multiple criteria decision analysis (MCDA) approaches are major parts of
decision and involve the selection of the best actions from a set of alternatives
analysis to evaluate against multiple criteria and also seek to take explicit account
of more than one criterion in supporting the decision process. Many existing
MCDA methods focus on certainty and uncertainty decision problems. The
criteria were evaluated separately as if they were independent of each other which
enable evaluation and ranking of many alternatives.

7

The general objective of MCDA is to assist a decision maker or a group of
decision about the problems they face to choose the best alternative from a range
of alternatives in an environment of conflicting and competing criteria such in the
way the idea of multiple criteria is considered, using computation of weights and
scoring with the mathematical algorithm, the model to describe the system of
preferences of the individual facing decision-making. The MCDA technique
selected will typically need to (Andrea De Monti at al., 2000):
•

Deal with complex situations (criteria), consider different scales and aspects
(geographical scales, micro-macro-link), social/technical issues and type of
data (uncertainties)

•

Involve more than one decision maker (stakeholder participation, actors,
communication, and transparency)

•

Inform stakeholders in order to increase their knowledge and change their
opinion and behavior (problem structuring, tool for learning, transparency)
The MCDA component consists of a collection preference structure

modeling techniques and associated in multi-criteria decision models. The
preference modeling techniques might include with criterion weighting techniques
and method as well as the methodology for generating the hierarchical value
structure of evaluation criteria, with these MCDA overcomes the limitations of
less structured methods, basic methods can be used to reduce complex problems
to a singular basis for selection of a preferred alternative. In some methodologies
when decide to use MCDA are similar steps of organization and decision matrix
construction. In another perspective different methods require diverse types of
value information and using some many algorithms. Several techniques use rank
options, with indicate some identify and a single maximum alternative, and others
differentiate between acceptable and unacceptable alternatives (Malczewski,
1999).
Another points of view that multi-criteria methods categorized as discrete or
continuous with calculate upon domain alternatives. In some cases the use of this
method does not always use the weights to combine several criteria to generate
aggregate score for each alternative. Using the basic approach is simple, very
stout in the case, it can be done without using a computer calculation, these

8

methods is best suited for a one-decision problem with several alternatives and
criteria.
In associate with GIS and MCDA method is not only to set the spatial
reference information that is required, but also to implement new methods of
analysis that allows information to get the most relevant and most appropriate
solutions in the search for necessary information. However, most of the MCDA
problem does not only consider quantitative criteria, but also qualitative, to make
some analysis and the appropriate criteria, which makes the problem becomes
complex and difficult to use as decision and analysis.
II.2.2 Ranking and Rating
There are two simple techniques that MCA utilises to identify and select
relevant Criteria & Indicator are Ranking and Rating. Ranking involves assigning
each decision element a rank that reflects its perceived degree of importance
relative to the decision being made. The decision elements can then be ordered
according to their rank (first, second etc.). Rating is similar to ranking, except that
the decision elements are assigned „scores‟ between 0 and 100. The scores for all
elements being compared must add up to 100. Thus, to score one element high
means that a different element must be scored lower (Mendoza, G. A., 1999).
There are three general steps in Criteria and Indicators (C&I) assessment. Multi
criteria analysis (MCA) has specific application as a decision making tool in steps
1 and 3.
1. The identification and selection of Criteria and Indicators.
2. The scoring of indicators based on the selected set.
3. The assessment of the system in terms of its overall performance at all levels of
the C&I hierarchy.
There are two different ways to rank a set of decision elements, Regular Ranking
and Ordinal Ranking. Regular Ranking assigns each element relevant to the
decision process a „rank‟ depending on its perceived importance. Ranks are
assigned according to the 9 point scale as shown in Table 1.

9

Table 1 Regular Ranking Value
1
Not
important

3
Moderately
important

5
Important

7
Very
important

9
Extremely
important

Ordinal Ranking is a technique where each expert is asked to put the list of
decision elements in order of importance. Unlike regular ranking where different
decision elements can be given the same ranking, ordinal ranking forces the
experts to put the elements in a hierarchy of importance; each element is deemed
more or less important relative to the other elements involved (Mendoza, G. A.,
1999).
Initial set of Criterias &
Indicators

Discard

Ranking and Rating
Process

Assign

General
Filter

Weighted Set of
Criterias & Indicators

Discarded Criterias & Indicators
(Low Relative Weight)

+

Fine
Filter

Relative Weights

+

Scores

=

Weighted Score

Assign

Inform Expert

Pairwise
Comparisons

Evaluate Performance of
Criteria & Indicators
Chosen

Track Source off
Inconsistency
Inconsistency Index
(CI)

If > 10% treshold

Legend

Process

Result

Figure 1 Figure application of MCA Techniques to the Selection and Scoring of
Criteria and Indicator (Mendoza, G. A., 1999)
II.3 Database Management System
A database is a collection of interrelated data organized in such a way that it
corresponds to the needs and structure of an organization and can be used by more
than one person for more than one application (Efraim Turban, 1993). The data in

10

the database are stored together with a minimum of redundancy to serve multiple
applications, so the database is independent of the computer program that uses it
and the type of hardware where it is stored. A database can be defined from
several perspectives (Fathansyah, 1999), such as:
- Collection of data group (archives) that related each other, which is organized
in such way so that in the future it can be utilized again quickly and easily.
- Collection of interrelated data kept together in such a way without unnecessary
redundancy, to fulfill many kinds of needs.
- Collection of files/tables/archives that related each other, kept in electronic
storage medium.
DBMS performs three basic functions. It enables storage of data in the
database, retrieval of data from the database, and control of the database.
II.3.1 Storage
DBMS varies the configuration of the stored data. Mainframe systems store
many large files, each containing many records, each record containing many data
items, and the data items containing many characters. The systems for
microcomputer offer more constrained capacities because of limited primary and
secondary storage spaces. This limitation is becoming less and less factor.
II.3.2 Retrieval
The feature of DBMS most visible to the user is data retrieval. Current
DBMS offer great flexibility in terms of how the information is retrieved and
displayed. With a sophisticated DBMS, the user can specify certain processing of
data and customize the output (e.g., reports or graphs) in terms of heading and
spacing.
II.3.3 Control
Much of the control activity of the DBMS is invisible to users. The users
ask for some information and receive it without knowing the process that the
DBMS has performed. The DBMS can be designed to screen each request for
information and determine that (1) the person making the request is indeed an
authorized user, (2) the person has access to requested file, and (3) the person has
access to the requested data items in the file. A mainframe DBMS might perform
all the control functions very well.

11

There are some capabilities of DBMS in DSS (Efraim Turban, 1993)
-

Captures/extract data for inclusion in a DSS database

-

Quickly updates (adds, deletes, changes) data records and files

-

Interrelates data from different sources

-

Quickly retrieves data from a database for queries and reports

-

Provides comprehensive data security (protection from unauthorized access,
recovery capabilities, etc.)

-

Handles personal and unofficial data so that users can experiment with
alternative solutions based on their own judgment

-

Performs complex retrieval and data manipulation tasks based on queries

-

Tracks usage of data.

II.4 Monitoring Coral reef
Managing the coral reef need to balance between sustainability and
conservation of coral reefs, therefore the relations between human behavior and
reef ecosystems are critical. Reefs condition is strongly influenced by human
activities and environmental conditions in which poverty level contained in the
coastal areas and small islands highly dependent on the presence of coastal and
marine resources. There are close links how coastal communities in the use of
coral reefs and social conditions of its economy.
Due communities are not yet know and understand the importance function
of coral reefs. Moreover, many institutions in the national and locally yet have
enough data and accurate about the potential and status of coral reefs and other
marine resources. Sustainable use and protection of coral reefs, policy makers
need to know (GCRMN, 2000):
-

Status of coral reefs and changes in the health of coral reef and reef fish.

-

Condition of the people that use and affect coral reef include the ability to
use, perception of management and characteristics of the people who feel
the impact of coral reef.

II.4.1 Monitoring with Remote Sensing Data
Coral reefs monitoring conducted by direct measurement method, field and
remote sensing technology and geographic information systems. Use of remote

12

sensing technology is one method more practical and efficient because it can
cover vast areas and distances (Lehmann at al., 1997, Stoffle at al., 1994).
Satellites collect data from extensive geographical areas in very short
periods. These data consist primarily of electronic records of the intensities of
electromagnetic radiation reflected or emitted from the earth's surface through the
atmosphere to the satellite. Taken repetitively, these data may help identify and
monitor changes in the average amount of radiation recorded from analytical units
called pixels. However, the satellites can neither interpret what is observed in
ecological terms nor explain what has caused the observed changes (Stoffle et al.,
1994).
Some combination methods and data analysis model has been carried out to
obtain the expected aims using of satellite imagery. This is closely related to the
ability of satellite imagery that can provide spatial information in serial and the
information contained in coral reefs. Application of the model was performed for
determine many marine protected areas and monitoring of coral reefs, and results
helpful for management of coral reefs (Scopélitis at al., 2007, Serge Andrefouet,
2006, Wood at al., 2007).
Numerous theoretical studies have been undertaken to obtain a model for
extracting bathymetry and substrate information from passive multispectral
remotely-sensed data (Jupp D.L.B., 1988, Lyzenga, 1978, Lyzenga, 1981). Simple
algorithms have been implemented in an attempt to map the bathymetry, assess
water turbidity, and map the type of substrate. Algorithms which have been used
successfully in the mapping of the coral reef substrate include band-ratioing and
the creation of pseudo-bands from the original spectral bands (Jupp D.L.B., 1988,
Jupp, 1985). However, the existence of water turbidity, the effects of the
atmosphere on the radiation emerging from the water column, and the mixing of
different reef substrates within a given pixel will often limit the effectiveness of
many such algorithms.
Some study have been conducted related to water zone study using Landsat
Satellite. For example, (Siregar V.P., 1996) conducted the coral reef ecosystem
classification using joint algorithmic band 1 and 2 (visible) from landsat-TM data,
(Jupp D.L.B., 1988) developed depth of penetration model for water depth crude

13

measurement using visible band and close infra red from Landsat-TM, and
(Lyzenga, 1978) made water column correction using seichi-disck transparency
(SDT) to show the transparency level of the water with visible band ratio.
Remote sensing has been touted to provide information on several
parameters that are of importance to reef management. Those are coral reef
boundaries, may be used for routing planning requirements and locating the
boundaries of management zoning schemes, geomorphologic zone of the reef (e.g.
reef flat, reef crest, spur and groove zone), ecological component and
determination of live-coral cover. Ecological component may be defined in
several ways, such as assemblages of coral species, assemblages of major reefdwelling organisms, or assemblages of species and substrata (Edmund P. Green at
al., 2000).

Figure 2 Cross Section Through a Coral Reef Showing the Major Zones
(Jos Hill at al., 2004)
II.4.2 Socio-economic Condition
Socio-economic conditions are a way to identify aspects of social, cultural,
economic and political conditions of individuals, groups, communities, and
organizations. There is no standard in examining the topic of socio-economic
conditions, but is commonly used for identification of topic such as the use of
resources, characteristics of stakeholders, gender issues, stakeholder perceptions,
organization and administration skills, traditional knowledge, service and public

14

facilities, components for use in market more broadly, outside the market value
and which are not used. Understanding socio-economic conditions are important
in the inventory, predict and manage coral reefs.
Information on socio-economic provide guidance to stakeholders for
(GCRMN, 2000):
-

Determine the relevant stakeholder groups, and concerned in the
management process. This will increase the legitimacy of that decision
making and adherence to rules and regulations become more stringent.

-

Determine the effects of management decisions to the stakeholders, which
will improve policy decisions to minimize impacts and maximize benefits
to stakeholders.

-

Shows the value of coral reef resources and services to the general public,
stakeholder groups and policy makers, which will generate greater support
for coral reef mana