Evaluation of Rubber Plantation Development using Geographic Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South Sumatera).

EVALUATION OF R GEOGRA

(Case Stu

BOGOR

OF RUBBER PLANTATION DEVELOPMENT OGRAPHIC INFORMATION SYSTEM AND

MULTI CRITERIA ANALYSIS

Study in Banyuasin Regency, South Sumatera)

MARTINI YULIA

GRADUATE SCHOOL

GOR AGRICULTURAL UNIVERSITY BOGOR

2011

STATEMENT

I, Martini Yulia, stated that this thesis entitled:

Evaluation of Rubber Plantation Development Using Geographic

Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South Sumatera)

Is a result of my own work under the supervision of the advisory board during the period February until August 2011 and that it has not been published. The content of the thesis has been examined by the advising the advisory board and external examiner

Bogor, July 2011

Martini Yulia G051090031

ABSTRACT

MARTINI YULIA, Evaluation of Rubber Plantation Development using Geographic Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South Sumatera). Under The Supervision of MUHAMMMAD BUCE SALEH AND ANTONIUS BAMBANG WIJANARTO.

The objective of the research is to evaluate of rubber plantation development in Banyuasin Regency using Geographic Information System and to analyze priority development of sub regency for rubber plantation using Analytical Hierarchy Process (AHP). Potential land for the development of rubber could be determined if soil and climate conditions are known. The soil and climate condition are linked to characteristics of rubber plantation. These relationships can produce a land suitability classification system, which aims to assess how far the level of suitability of the land to plant rubber. The method used consisted of three steps: (1) land suitability analysis from available maps (climate, soil, topography and existing land use): (2) productivity analysis of rubber from available production data in 2009: (3) Rubber area development by using Multi Criteria Analysis (MCA). The result of this research showed that all the areas of Banyuasin Regency are suitable for rubber plantation development. It was found that about 15.4% or 164,201 ha of Banyuasin Regency are highly suitable (S1) and about 84.6% or 904,681 ha are moderately suitable (S2) for rubber plantation. Then the existing rubber was evaluated the productivity of rubber which produce suitable areas with high productivity about 21,703 ha and low productivity about 31,021 ha. This research also produced areas suitable for planting rubber which are considered social and economic factors about 51,960 ha. The total area of priorities for rubber plantation development is 51,960 ha or 4.87% from area of Banyuasin Regency.

ABSTRAK

MARTINI YULIA, Evaluasi Pengembangan Perkebunan Karet Menggunakan Sistem Informasi Geografis dan Analisis Multi Criteria (Studi Kasus di Kabupaten Banyuasin, Sumatera Selatan). Dibimbing oleh MUHAMMAD BUCE SALEH dan ANTONIUS BAMBANG WIJANARTO.

Tujuan dari riset ini adalah untuk evaluasi perkembangan perkebunan karet di Kabupaten Banyuasin menggunakan system informasi geografis dan untuk analisis prioritas kecamatan untuk perkembangan perkebunan karet menggunakan Process Hirarki Analitik (AHP). Potensi lahan untuk pengembangan tanaman karet dapat ditentukan jika keadaan tanah dan iklim diketahui terlebih dahulu.Kondisi tanah dan iklim tersebut berkaitan dengan sifat-sifat yang dikehendaki tanaman karet. Hubungan tersebut menghasilkan suatu sistem klasifikasi kesesuaian lahan, yang tujuannya untuk menilai seberapa jauh tingkat kecocokan suatu lahan terhadap tanaman karet. Metode yang digunakan terdiri dari 3 langkah: (1) Analisis kesesuaian lahan dengan menggunakan peta-peta yang tersedia (iklim, tanah, topografi dan penggunaan lahan): (2) Analisis produktivitas karet menggunakan data produksi tahun 2009 yang tersedia: (3) Penambahan luas karet menggunakan Analisis Multi Criteria. Hasil dari penelitian ini menunjukkan bahwa semua area Kabupaten Banyuasin sesuai untuk pengembangan perkebunan karet, sekitar 15.4% atau 164,201 ha dari luas kabupaten banyuasin adalah sangat sesuai (S1) dan sekitar 84.6% atau 904,681 ha adalah sesuai (S2) untuk perkebunan karet. Kemudian model yang digunakan untuk mengevaluasi tanaman karet yang ada dan produktivitas menghasilkan area sesuai dengan produktivitas tinggi sekitar 21,703 ha dan produktivitas rendah sekitar 31,021 ha. Penelitian ini juga menunjukkan bahwa area baru untuk menanam karet dengan pertimbangan faktor ekonomi dan social adalah sekitar 51,960 ha. Total prioritas area tanaman karet untuk dikembangkan di Kabupaten Banyuasin adalah sekitar 51,960 ha atau 4.87%.

SUMMARY

MARTINI YULIA, Evaluation of Rubber Plantation Development using Geographic Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South Sumatera). Under the Supervision of MUHAMMMAD BUCE SALEH AND ANTONIUS BAMBANG WIJANARTO.

Rubber is an export commodity that is able to contribute to the increase in Indonesia's foreign exchange. Foreign exchange earnings from this commodity in 2004 reached U.S. $2.25 billion, which represents 5% of non-oil foreign exchange earnings. National rubber production in 2005 reached approximately 2.2 million tons (Hanspari, 2010). Over the last five years from the year 2005 to 2009, exports of rubber and rubber products would average $ 5.6 billion per year, with a growth of 10 percent. Exports of rubber and rubber products reached USD522.8 million, an increase of 84 percent from the same month in 2009.

Rubber plants originated from tropical areas in the Amazon Basin, Brazil with rainfall 2000 - 3000 mm/year and the rainy days of 120 - 170 days/year (Sutardi, 1981). Rubber trees grow in areas between 10o North and 10o South (Moraes, 1977). Most of Indonesian rubber plantations are located in Sumatera and Kalimantan, with rainfall ranging from 1500 to 4000 mm/year with an average of 0 - 4 months in dry months per year

Banyuasin is one of the regencies in South Sumatera. Banyuasin area has the potential for agriculture and plantation. From the total area of 11.832,99 km2, about 47 percent is agricultural and plantation areas. Contributions to local income of Banyuasin Regency are 35 percent from the agricultural sector, 21% from industrial sector, and 15% from trading. Agriculture of this regency has paddy field of 596,303.36 tons. The productions of oil palm and rubber are 130,228.11 tons and 89,640.50 tons, respectively. Rubber plants are very potential to be developed in this area. Rubber plantations in Indonesia are generally composed of smallholder rubber (85%) and the rest (15%) are state and private plantations. (Bappeda and BPS Statistic of Banyuasin, 2008).

The objectives of this research are to study evaluation of rubber plantation development in Banyuasin Regency using Geographic Information System and to analyze priority development of sub regency for rubber plantation using Analytical Hierarchy Process (AHP). The results of early studies based on the literature, statistic data, physical aspects, aspects of social and economic aspects.

The study covers the period of February 2010 to July 2011. The research location was in the Banyuasin regency, South Sumatera Province. The coordinate geographic position was in latitude 1018’00” – 4000’00” South and longitude between104040’00 – 105015’00” East. Banyuasin Regency consists of 15 Sub Regency.

The main stages carried out in this study are as follows: (1) analysis of Land Suitability for rubber plantation from available maps (climate, soil, topography and existing land use); (2) productivity analysis of rubber from available data of production in 2009; (3) Rubber area development by using Multi Criteria Analysis (MCA).

The land suitability result shown that all areas in Banyuasin Regency are suitable for rubber plantation. The areas were divided into two parts: highly suitable area (S1), and moderately suitable area (S2). It was found that about 15.4% or 164,201 ha of Banyuasin Regency are highly suitable (S1) and about 84.6% or 904,681 ha are moderately suitable (S2) for rubber plantation. Spatial analysis resulted to suitable area for rubber and the largest area from the total land is moderately suitable (S2).

From the result of classification of plantation and validation using GPS coordinate of rubber areas is about 53,892 ha and oil palm areas about 56,728 ha. The largest area from total of existing rubber areas (S1) in Banyuasin III Sub Regency is about 8,310 ha and for S2 in Banyuasin I Sub Regency about 24,684 ha, then the smallest area from the total of existing rubber areas (S1) in Rambutan Sub Regency about 4.24 ha and for S2 in Banyuasin III Sub Regency about 0.11 ha.

Based on Indonesian Rubber Statistics (2008), high productivity of rubber plantation is more than 1.5 ton/ha/year, the average productivity of rubber plantation in Banyuasin Regency is 1.8 tons/ha/year, the productivity of rubber analysis shows that productivity condition of suitable area planted with rubber in Banyuasin regency divided into four parts: highly suitable areas planted with rubber and high productivity (S1 rubber, high productivity) about 17,183 ha, highly suitable areas planted with rubber and low productivity (S1 rubber, low productivity) about 158 ha, moderately suitable areas planted with rubber and high productivity (S2 rubber, high productivity) about 4,520 ha, moderately suitable about areas planted with rubber and low productivity (S2 rubber, low productivity) about 30,963 ha.

The next analysis was performed using ratings with AHP method to expand plantation areas. This method considered social and economic factors. This analysis has a purpose to determine priorities of sub regency for rubber development. Social factor used several variables such as area of rubber and number of rubber farmer. Economic factor used also two variables i.e. ratio income of rubber with non rubber and ratio cost of rubber with non rubber.

In rating models, each variable should be categorized into several classes (4 – 5 classes). This classes show the conditions of each variables (such as highly suitable, moderately suitable, marginally suitable and not suitable). For number of rubber farmer was classified into very high number of farmers (vhn), high number of farmers (hn), moderate number of farmers (mn), small number of farmers (sn) and very small number of farmer (vsn). This variable is indicated rubber is socially accepted if the number of rubber farmer is greater. For Area of rubber was claaified into very large, large, medium, small and very small. This variable is indicated rubber is socially accepted if the area of rubber is greater. Then for ratio income of rubber with non rubber was classified into very high, high, medium, low and very low. This variable is indicated rubber is economically accepted if the income of rubber is greater and for ratio cost of rubber with non rubber was classified into very large, large, moderate, small and very small. This variable is indicated rubber is economically accepted if the cost of rubber is smaller (please see Appendix 5.

Rating models was evaluated all sub regency of Banyuasin Regency i.e. fifteen (15) sub regency. The result of rating models is shown in Table 17, in

Table 17 shows each sub regency has value total ranging from 0 to 1 and shows also that Rambutan Sub Regency, Betung Sub Regency, Rantau Bayur Sub Regency and Banyuasin III sub regency are top four in priorities of sub regency for rubber plantation development, Rambutan sub regency has total value 0.640, Betung sub regency has total value of 0.682, Rantau Bayur sub Regency has total value of 0.593 and Banyuasin III Sub Regency has of value 0.588. That is meaning based on consideration social and economic factors, the top four in priorities of sub regency has positive impact than other sub regency, so considerately Rambutan Sub Regency, Betung Sub Regency, Rantau Bayur Sub Regency and Banyuasin III sub regency as area of priorities for rubber plantation development.

The priorities of sub regency for rubber plantation development are Rantau Bayur Sub Regency about 19,216 ha or 1.8%, followed by Banyuasin III Sub Regency about 6,838 ha or 0.6%, Betung Sub Regency about 7,337 ha (0.7%) and Rambutan Sub Regency about 18,569 ha or 1,7%. The total area of priorities for rubber plantation development is 51,960 ha or 4.87% from areas of Banyuasin Regency.

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EVALUATION OF RUBBER PLANTATION DEVELOPMENT USING GEOGRAPHIC INFORMATION SYSTEM AND

MULTI CRITERIA ANALYSIS

(Case Study in Banyuasin Regency, South Sumatera)

MARTINI YULIA

A Thesis submitted for the degree of Master of Sciences in Information Technology for Natural Resources Management Program Study

GRADUATE SCHOOL

BOGOR ANGRICULTURAL UNIVERSITY BOGOR

Research Title : Evaluation of Rubber Plantation Development Using Geographic Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South Sumatera)

Student Name : Martini Yulia Student ID : G051090031

Study Program : Master of Science in Information Technology for Natural Resource Management

Approved by, Advisory Board

Dr. Muhammad Buce Saleh Dr. Antonius Bambang Wijanarto Supervisor Co-Supervisor

Endorsed by,

Program Coordinator Dean of Graduate School

Dr. Ir. Hartrisari Hardjomidjojo, DEA Dr. Ir. Dahrul Syah, M. Agr. Sc

Date of Examination Date of Graduate: July 29, 2011

ACKNOWLEDGMENTS

Alhamdulillah, Thanks to The Almighty ALLAH SWT, which has given me the opportunity and ability to complete this thesis. The success of this study would not have been possible without various contribution and support from many people and I will not be able to mention them one by one. Of course, I would like to express my highly appreciation to all of them.

I wish to thank my supervisor, Dr. Muhammad Buce Saleh and my co-supervisor, Dr. Antonius Bambang Wijanarto for their guidance, technical comment and constructive critics.

I would like to thank for Balai Besar Sumber Daya Lahan Pertanian (BBSDLP) for support me in obtained soil data.

I would like to thank to all MIT secretariat staff who support our administration and facility. I would also like to thank all MIT lecturers who taught me with very important knowledge during my study.

Thanks are also due to all my colleagues in MIT for helping, supporting, and togetherness in finishing our assignment and study.

Finally, I would like to thank to my lovely husband Ir. Mattobi’i, MP, my lovely children Aisyah, Azi, Annisa and my parents for all their moral support, patience, prayer and love during my study.

Hopefully, this thesis could give positive and valuable contribution for anyone who reads it.

CURRICULUM VITAE

Martini Yulia was born in Palembang, South Sumatera, Indonesia on July 7th 1968. She graduated from Sriwijaya University, Faculty of Teachership Education, at Biology Program Study in 1991. She was entered the IPB Graduate School in year 2009. She was enrolled as private student in Master of Science in Information Technology for Natural Resources Management, Bogor Agricultural University in 2009, and completed her master study in 2011. Her final thesis is “Evaluation of Rubber Plantation Development Using Geographic Information System and Multi Criteria Analysis (Case Study in Banyuasin Regency, South-Sumatera)”.

i TABLE OF CONTENTS

TABLE OF CONTENTS ... i

LIST OF TABLES ...iv

LIST OF FIGURES ... v

LIST OF APPENDICES………..………..…vi

I. INTRODUCTION ... 1

1.1 Background………...1

1.2 Problem Statement………....2

1.3 Objectives………...3

1.4 Study Question………...3

1.5 Scope of the Research………...3

1.6 Study Output………...……..3

II. LITERATURE REVIEW ... 4

2.1 The Potential of Rubber……….4

2.1.1 Development of Rubber Plantation Area……….5

2.1.2 Development of Rubber Production………... .6

2.2 Basic Requirements for Rubber Plantation………. .8

2.2.1 Climate Requirements………...8

2.2.1.1 Rainfall……….8

2.2.1.2 Temperature………... .8

2.2.2 Landscape and Soil ………...………9

2.2.2.1 Topography………...9

2.2.2.2 Soil Texture……….10

2.2.2.3 Soil Dranage………10

2.3 Land Suitability for Rubber Plantation………...11

2.4 Geographic Information System……….14

2.5 Multi Criteria Decision Analysis (MCDA)……….15

2.6 Spatial Multi Criteria Analysis………15

ii

2.8 Rating (Absolute Measurement)………..19

2.9 Supervised Classification………19

III.METHODOLOGY………...21

3.1 Time and Location………...21

3.2 Data and Tools……….22

3.2.1 Supporting Data ... 22

3.2.2 Hardware and Software ... 23

3.3 Methods………...23

3.3.1 Land Suitability Analysis for Rubber Plantation ... 23

3.3.2 Analysis of Existing Land Use Types ... 27

3.3.3 Existing of Rubber Plantation ... 28

3.3.4 Productivity of Rubber Analysis ... 28

3.3.5 Multi Criteria Analysis ... 29

IV.RESULT AND DISCUSSION……….32

4.1 General Condition of the Study Area………..32

4.1.1 Topography ... 32

4.1.2 Climate ... 32

4.1.3 Land Use and Land Cover ... 32

4.1.4 Demography Condition ... 33

4.2 Land Suitability Analysis for Rubber Plantation………33

4.2.1 Temperature ... 34

4.2.2 Rainfall ... 34

4.2.3 Soil Texture ... 36

4.2.4 Soil Drainage ... 36

4.2.5 Topography ... 37

4.2.6 Overlay Process ... 38

4.3 Existing of Rubber Plantation……….39

4.4 Productivity of Rubber Plantation………...42

4.5 Existing of Non Rubber………...45

4.6 Development Area of Rubber Plantation………47

iii

V. CONCLUSION……….52

5.1 Conclusion………...52

5.2 Recommendation……….52

REFFERENCES..…..……….54

iv LIST OF TABLES

Table 1. Development of Rubber Plantation Area in Banyuasin Regency…….5

Table 2. Development of Rubber Production in Banyuasin Regency……….. ..7

Table 3. Influence of Temperature on Growth and Production of Rubber….. ..9

Table 4. Classification of Land Suitability for Rubber Plantation………13

Table 5. Random Consistency Index (RI)……….18

Table 6. Supporting Data Required……….. 22

Table 7. Hardware and Software……….. 23

Table 8. Structure of Suitability Classification………. 25

Table 9. Relations Between Suitability Grades and Classes……….26

Table 10. Scale and Definition of Pairwise Comparison……….. 30

Table 11. Number of Population, Total Villages, Total Area and Average Number of Population per square km by Sub regency in Banyuasin regency……… 33

Table 12. Summary of Climate Condition from Different Station…………...34

Table 13. Existing of Rubber in Banyuasin Regency………... 41

Table 14. Condition of Productivity of Rubber in 2009………... 43

Table 15. Summary Areas of Suitable, Planted with Rubber and Productivity of Rubber………..……….44

Table 16. Existing of Non Rubber in Banyuasin Regency………... 46

Table 17. Priorities of Rubber in Sub Regency……… 49

v LIST OF FIGURES

Figure 1. Development of Rubber Plantation Area in Banyuasin Regency…. ..6

Figure 2. Development of Rubber Production in Banyuasin Regency………. ..7

Figure 3. The Study Site………... 21

Figure 4. Methodology Flowchart of the Research……….. 24

Figure 5. Flowchart of Land Suitability for Rubber Plantation……… 26

Figure 6. Area Distribution of Land Use (Hectares)……….27

Figure 7. Land Use Map of Banyuasin Regency……….. 28

Figure 8. Relationship among Goal, Criteria, Sub Criteria and Alternatives in AH..30 Figure 9. Map of Temperature in Study Area………... 35

Figure 10. Map of Rainfall in Study Area……… 35

Figure 11. Map of Soil Texture in Study Area………. 36

Figure 12. Map of Soil Drainage in Study Area………... 37

Figure 13. Land Suitability for Rubber Plantation………39

Figure 14. Plantation Existing in Banyuasin Regency………..40

Figure 15. Rubber Existing in Banyuasin Regency……….. 40

Figure 16. Area of Suitable Map, Rubber and Productivity of Rubber……… 45

Figure 17. Existing of Non Rubber in Banyuasin Regency……….. 46

Figure 18. Existing of Shrub in Sub Regency………...47 Figure 19. Priorities of Sub Regency for Rubber Plantation Development…. 50

vi LIST OF APPENDICES

Appendix 1. Number of Rubber Farmers……….………...59

Appendix 2. Ratio of Income Rubber with Non Rubber………..….…60

Appendix 3. Ratio of Cost Rubber with Non Rubber ……….……….…61

Appendix 4. Pairwise Comparison Method and Consistency Ratio (CR)…....62

Appendix 5. Classification in Ratings….……….………...63

Appendix 6. Final Periorities of Alternatives……….…...………....64

Appendix 7. Questionnaire for Expert Group…….……….……….…65

Appendix 8. Pairwise Comparison by Expert Choice.………...………...76

Appendix 9. Ratings Method by Expert Chioce………...……….77

1

I. INTRODUCTION

1.1 Background

Indonesia has a wide range of climate, from wet tropical to semi-arid. Rainfall varies according to time and place, while air temperature and radiation are relatively constant throughout the year because Indonesia is located on the equator. Air temperature variations are caused by differences in altitude.

Rubber plants originated from tropical areas in the Amazon Basin, Brazil with rainfall 2000-3000 mm/year and the rainy days of 120-170 days/year (Sutardi, 1981). Rubber trees grow in areas between 10o North and 10o South (Moraes, 1977). Most of Indonesian rubber plantations are located in Sumatera and Kalimantan, with rainfall ranging from 1500-4000 mm/year with an average of 0-4 months in dry months per year.

Potential land for the development of rubber could be determined if soil and climate conditions are known. The soil and climate condition are linked to characteristics of rubber plantation. These relationships can produce a land suitability classification system, which aims at assessing how far the level of suitability of the land to plant rubber (Thomas, 1995).

Land condition in Banyuasin Regency consists of majority wetlands and swamps, while rubber plants are suitable to be grown on dry land. However, many wetlands have been converted to rubber plantations, because the soil has become dry or wet land and dry land is not submerged in water (Media Perkebunan, 2008).

Banyuasin area has the potential for agriculture and plantation. From the total area of 11.832,99 km2, about 47 percent is agricultural and plantation areas. Contributions to local income of Banyuasin Regency are 35 percent from the agricultural sector, 21% from industrial sector, and 15% from trading. Agriculture of this regency has paddy field of 596,303.36 tons. The productions of oil palm and rubber are 130,228.11 tons and 89,640.50 tones, respectively. Rubber plants

2

are very potential to be developed in this area. Rubber plantations in Indonesia are generally composed of smallholder rubber (85%) and the rest (15%) are state and private plantations. (Bappeda and BPS Statistic of Banyuasin, 2008).

Since 2003, the program on replanting the old rubber plantations was carried out covering a target area of 10,000 ha, because, about 10% of 84,000 ha of rubber plantation consists of old trees whose production is not optimal anymore and must be replanted. In 2003, Banyuasin government provided seeds for replanting an area of 400 hectares. The seeds for replanting aid program in 2004 covers an area of 400 ha (Bappeda and BPS Statistic of Banyuasin, 2008).

In general, GIS (Geographical Information System) is a computer-based information system that combines elements of the map (geographical) and information about the map (data attributes) that are designed to obtain, process, manipulate, analyze, demonstrate and display spatial data to complete the planning, process and investigation of the problem.

Based on the potential of rubber plantations in Banyuasin Regency, it is necessary to do data processing and analyzing the potential of rubber plantation areas using GIS and multi criteria method. This is very helpful for policy makers of local governments for the development and production increase of rubber. 1.2 Problems Statement

Plantation sectors consisted of the smallholders, government plantation and private plantations. Among the potential commodities to be developed are rubber and oil palm.

The Regional Spatial Planning (RTRW) of Banyuasin Regency are policy, approach and spatial development strategy to achieve the goals of qualified spatial land utilization. The current land use development in Banyuasin Regency needs evaluation and consideration about rubber plantation development in suitable land. Based on this perspective in mind, we conducted evaluation of rubber plantation development to supportland use planning of Banyuasin Regency. This

3

study is focused on land suitability analysis, productivities analysis, and social-economic analysis using multi criteria method.

1.3 Objectives

The objectives of this study are: to evaluate the suitability of rubber plantation development in Banyuasin Regency using Geographic Information System and multi criteria method. The additional objective is to evaluate priority development of sub regency for rubber plantation using Analytical Hierarchy Process (AHP).

1.4 Study Question

To achieve the aforementioned study objectives in the previous section, the research questions of this study are:

1. What was done if the land is not suitable but planted with rubber? 2. What was done if the land is suitable but planted with rubber? 3. What was done if the land is suitable but not planted with rubber? 4. Where is the priority of areas for rubber plantation development?

5. How many sub regency belong to priority areas for rubber plantation development?

1.5 Scope of the Research

1. The study area is in Banyuasin Regency area located in South Sumatra. 2. This study analyzed rubber plantation development.

3. This study analyzed the priority of development area for rubber plantation using multi criteria method.

1.6 Study Output

The main output this study is; (1) Land suitability for rubber plantation map based on physical factors; (2) The table and map of productivity of rubber plantation based on the statistic data; (3) The priority map of sub regency for rubber plantation development based on multi criteria analysis.

4

II. LITERATURE REVIEW

2.1 The Potential of Rubber

Rubber is an export commodity that is able to contribute to the increase in Indonesia's foreign exchange. Foreign exchange earnings from this commodity in 2004 reached U.S. $2.25 billion, which represents 5% of non-oil foreign exchange earnings. National rubber production in 2005 reached approximately 2.2 million tons (Hanspari, 2010). Over the last five years from the year 2005-2009, exports of rubber and rubber products would average $ 5.6 billion per year, with a growth of 10 percent. Exports of rubber and rubber products reached USD522.8 million, an increase of 84 percent from the same month in 2009.

A number of locations in Indonesia has state land suitable for rubber plantations, mostly in Sumatra and Kalimantan. The area of rubber plantations in 2005 recorded more than 3.2 million ha scattered throughout the territory of Indonesia. Among them 85% are rubber plantation owned by the people, and only 7% of the country estates and 8% large plantations owned by private sectors. Rubber production in the year 2005 reached 2.2 million tons. This amount will be increased further still by doing a rejuvenating and empowering of agricultural lands owned by farmers as well as vacant land/non-productive that is suitable for rubber plantations (Anwar, 2006).

New paradigm that has been agreed in rubber plantation development is not only to produce latex, but also to produce rubber wood. The goal is to increase land productivity, increase revenue, and to increase their competitiveness. To optimize the results of latex and rubber wood, technical aspects of cultivation needs to be reviewed such as cropping system/population per hectare and type of clones. The volume of rubber wood obtained at the rejuvenation, with initial population 500-550 trees/ha is 180-200 m3/ha. Without prejudice to the latex, volume of wood could be improved to become ±350 m3/ha using plant regulating system, enhance the initial population, and by using suggestion clone producing

5

wood-latex, such as IRR 5, IRR 21, IRR 32, IRR 39 , IRR 42 and IRR 118 (Siagian et al, 2003).

2.1.1 Development of Rubber Plantation Area

Development of rubber plantation area in Banyuasin Regency during last four years has increased. In 2007, rubber plantations in Banyuasin Regency occupied an area of 100,536.78 ha, then increased in 2008 to 101,149.30 ha or an increase of 0.61%. Whereas in 2009 the total areas of rubber plantations of Banyuasin Regency increased to 0.39 percent or 101,542.00 hectares, but in 2010 the total areas of rubber plantations Banyuasin Regency decreased -0.87% or 100,653.59 ha. The development of rubber plantation area is shown in the Table 1.

Table 1 Development of Rubber Plantation Area (Ha) in Banyuasin Regency, 2007-2010

*) preliminary

Based on the exertion status, rubber plantations in Banyuasin Regency consist of three groups, namely smallholders, government plantation and private plantation. In 2008, the total rubber plantation areas in Banyuasin Regency was 101,149.30 ha with the breakdown as follows; 88,386.00 ha (87.38%) smallholders plantation, government plantation 7,383.00 ha (7.29%), and private plantation 5,380.30 ha (5.32 %). The development of rubber plantation based on the exertion status year 2007-2010 is shown in Figure 1.

Year Smallholders Government Plantation

Private

Plantation Total

Growth (%) 2007 87,386.00

7,752.00 5,398.78

100,536.78 83.36 2008 88,386.00

7,383.00 5,380.30

101,149.30 0.61 2009 88,875.00

7,372.00 5,295.00

101,542.00 0.39 2010*) 89,307.00

5,986.59 5,360.00

Figure 1 Developm 2.1.2 Development of R

Development of four years has increased increased to 2.49% in 2 increased 123,635.00 ton 2.63% or 126,973.00 to 2010 is shown in Table 2 Percentage of ru 87.64% of the total rubb of about 77.55% of the It could be concluded th is generally lower than private plantation. The d in Figure 2. In 2009, t with the breakdown is government plantation about 13,322.00 tons (10

-10,000.00 20,000.00 30,000.00 40,000.00 50,000.00 60,000.00 70,000.00 80,000.00 90,000.00 2007

ment of Rubber Plantation Area in Banyuasin Reg of Rubber Production

of rubber plantation in Banyuasin Regency durin ed. In 2007 production of rubber was 114,363.0

2008 i.e 117,283.00 tons. In 2009, production tons (5.14 %). Then in 2010, production of rubber

tons. Development of rubber production from e 2.

rubber plantation areas cultivated by smallholde bber plantation areas in Banyuasin Regency with e total rubber plantation production in Banyuasin that the productivity of rubber plantation from sma

an the productivity of government plantation e development of rubber production in 2007 - 201

the total production of rubber was about 123,6 is follows; smallholders about 91,988.00 tons n about 18,325.00 tons (14.81%) and private

10.78%).

2008 2009 2010

Smallholders Government Pl Private Plantat

6

egency

ring the last .00 tons and on of rubber ber increased m 2007 until

ders is about production sin Regency. smallholders as well as 010 is shown ,635.00 tons s (74.40%), te plantation nt Plantation ntation

Table

*) preliminary

Figure 2 Dev The current con smallholders, governme production growth of sma the rubber production private plantation decre production of rubber sho plantations are old, da rejuvenation. -10,000.00 20,000.00 30,000.00 40,000.00 50,000.00 60,000.00 70,000.00 80,000.00 90,000.00 100,000.00 2007 Year Smallholders 2007 92,153.00 2008 94,546.00 2009 91,988.00 2010*) 95,298.00

ble 2 Development of Rubber Production in Banyuasin Regency, 2007-2010

evelopment of Rubber Production in Banyuasin R ondition showed that rubber agribusiness is ma

ment plantation and private plantation. Th smallholders was positive, but slow i.e 0.7 % per y n of government plantation decreased about 9 reased 1.06% per year. Therefore, support to m hould be given to smallholders. Rubber trees in s damaged and unproductive about 8,712.00 hec

2008 2009 2010

Smallholders Government P Private Plantat rs Government

Plantation

Private

Plantation Total 12,352.00 9,858.00 114,363.00 12,648.00 10,089.00 117,283.00 18,325.00 13,322.00 123,635.00 18,342.00 13,333.00 126,973.00 7 Regency managed by The rubber r year, while 9.43% and manage the smallholder ectares need nt Plantation ntation Growth (%) 0.9 2.49 5.14 2.63

8

2.2 Basic Requirements for Rubber Plantation 2.2.1 Climate

2.2.1.1 Rainfall

The major climatic factor which influences plant growth is rainfall (also called precipitation) from which the required amount of water can be supplied to the plant. If there is no enough rainfall available in a particular region, water should be supplied by a combination of rainfall and irrigation. If the rainfall is sufficient to cover the water needs of the plant, irrigation is not required. If there is no rainfall, the water for plant need has to be supplied by irrigation.

Water is the key to productive agriculture. The quantity of water needed to grow a plant will depend upon soil and climatic conditions as well as the nature of the plant itself. Excess water must be drained away before plant roots suffer from lack of aeration; yet soil moisture must be retained at content sufficiently high that the plant will not suffer during dry plant periods.

Minimum rainfall for rubber plant is 1500 m / year. In general rubber plant can grow well in the range of 1500 - 3000 mm / year rainfall. The amount of evapotranspiration or water requirement of rubber is equivalent to evaporation measured by pan of class A or 3 mm - 5 mm per day for the condition in Indonesia (Haridas, 1985). Rainfall of 100 mm - 150 mm will be enough for the water need of the rubber plant for 1 month (Rao and Vijayakumar, 1992). Excessive rainfall may disturb harvest caused by disease attack. On the other hand, drought would suppress growth and rubber production (Thomas, 1995). 2.2.1.2 Temperature

Temperature is one of the most important climate factors in the development. It favors rate of photosynthesis from which the plant can use the necessary food for the growth. The temperature requirement of one plant is different from another depending on the type of plant and origin of a particular plant.

9

Air temperature in the lowland tropical region is about 28oC and the air temperature decreases about 0.6oC for every increase of 100 m. Air temperature in the lowland tropical region is about 28 and the air temperature decreases about 0.6 for every increase of 100 m. Influence of temperature on growth and production of rubber is shown in Table 3.

Table 3 Influence of Temperature on Growth and Production of Rubber

Temperature (o C) Influence Growth and Production 5

10 18-24 27-33 35 40

Crop damage because low temperature Photosynthesis stopped

The optimum flow of latex The optimum for Photosynthesis Stomata close

High respiration and low photosynthesis rate

2.2.2 Landscape and Soil 2.2.2.1 Topography

Topography is often a major factor in irrigation evaluation as it influences the choice of irrigation method, drainage, erosion efficiency, costs of land development, size and shape of fields, labour requirements, range of possible plants, etc. Slope is one of the aspects of topography that have a special bearing on irrigation suitability.

Slopes of 50% of more are commonly surface irrigated in traditional Asian terraced system; however, such land would generally not be considered-suitable for development today. Slope gradient is the inclination of the surface of the soil from the horizontal. It is generally measured with a hand level. The difference in elevation between two points is expressed as a percentage of the distance between those points. If the difference in elevation is 1 meter over a horizontal distance of 100 meters, slope gradient is 1 percent. A slope of 45o is a slope of 100 percent,

10

because the difference in elevation between two points is 100 meters apart horizontally is 100 meters on a 45o slope.

2.2.2.2 Soil Texture

The texture of a soil is determined by the relative proportion of clay, silt and sand particles. Texture is most easily determined in the field by pressing and rubbing moist soil between the fingers. Texture classes are:

o Coarse texture: sands, loamy sand and sandy loams with less than 18% clay, and more than 65% sand.

o Medium texture: sandy loams, loams, sandy clay loams, silt loams with less than 35% clay and less than 65% sand; the sand fractions may be as high as 82% if a minimum of 18% clay is present.

o Clays, silty clays, sandy clays, clay loams and silty clay loams with more than 35% clay.

Good soil texture for rubber plant is clay soil texture, while sandy soil is adverse. Soil with clay texture has a capacity to hold water and nutrients better than sandy soil texture (Yew, 1991).

2.2.2.3 Soil Drainage

Natural soil drainage refers to the average wetness or dryness of a soil and may be a clue to soil permeability. The colors of topsoil and sub soil are clues to interval drainage.

o Well Drained: Land has hydraulic conductivity medium and water holding capacity is medium, moist, but not enough to wet ground near the surface. This land suitable for various crops.

o Moderately Well Drained: Land has hydraulic conductivity moderate to somewhat low and water holding capacity is low, wet ground near surface. This land suitable for various crops.

o Somewhat Poorly Drained: Land has hydraulic conductivity somewhat low and water holding capacity is low to somewhat low, wet

11

ground to surface of land. This land suitable for paddy rice and other crops fraction.

o Somewhat Excessively Drained: Land has hydraulic conductivity high and water holding capacity is low. This land suitable only for some plants that without irrigation.

o Poorly drained: Land has hydraulic conductivity low and water holding capacity is low to very low. Wet ground for long time on surface. The land suitable for paddy rice and some plants other.

o Excessively Drained: Land has hydraulic conductivity high to very high and water holding capacity is low. The land not suitable for crops without irrigation.

Rubber plants require water drainage is well. The flood condition is not conducive to the growth of rubber plants. Soil drainage range of good (well) and moderately well is ideal range for rubber plants. At soil drainage is poorly and excessively drained the growth and production of rubber is very low (Thomas, 2008).

2.3 Land Suitability for Rubber Plantation

Land suitability is the ability of a given type of land to support a defined use. The process of land suitability classification is the evaluation and grouping of specific areas of land in terms of their suitability for a defined use. The principles of sustainable development make land-use suitability analysis become increasingly complex due to consideration of different requirements/criteria. It includes consideration not only inherent capacity of a land unit to support a specific land use for a long period of time without deterioration, but also the socio-economic and environmental costs (Hananto, 2007).

The concept of sustainable agriculture or farming involves producing quality product in an environmentally benign, socially acceptable and economically efficient way (Addeo et al., 2001 in Hananto, 2007), i.e. optimum utilization of the available natural resource for efficient agricultural production.

12

Each plant species requires definite soil and site conditions for its optimum growth. Although some plants may be found to grow under different soils and extreme agro-ecological conditions, yet not all plants can grow on the same soil and under the same environment. Most of the plant species need well drained, moderately fine to medium texture soils, free of salinity and having optimum physical environment (Mishra, 2007).

The land suitability classification, using the guidelines of FAO (1976) is divided into Order, Class, Sub Class, and Unit. Order is the global land suitability group. Land suitability Order is divided into S (Suitable) and N (Not Suitable). The process of land suitability classification is the appraisal and grouping of specific land in terms of their suitability for defined uses. Suitability can be scored based on factor rating or degree of limitation of land use requirements when matched with the land qualities. In other words land suitability evaluation is a comparison and matching of land utilization type requirements with land unit characteristics. Land suitability classes reflect degrees of suitability. That is defined as the following:

Class S1 Highly Suitable: Land having no significant limitation or only have minor limitations to sustain a given land utilization type without significant reduction in productivity or benefits and will not require major inputs above acceptable level.

Class S2 Moderately Suitable: Land having limitations which in aggregate are moderately severe for sustained application of the given land utilization type; the limitations will reduce productivity or benefits and increase required inputs to the extent that the overall advantage to be gained from the use, although still attractive, will be appreciable compared to that expected from Class S1 land. Class S3 Marginally Suitable: Land having limitations which in aggregate

are severe for sustained application of the given land utilization type and will so reduce productivity or benefits, or increase required inputs, that any expenditure will only be marginally justified.

13

Class N Not Suitable as the range of inputs required is unjustifiable. (Ritung, 2007)

Land quality is the complex attributes of lands and contains one or more land characteristics. Important land characteristics in any land evaluation include topography, soil, and climate. These, especially topography and soil, are important components in determining land units. Important land characteristics in any land evaluation include topography, soil, and climate. These, especially topography and soil, are important components in determining land units. The relationship of land quality and land suitability classification is described in Table 4.

Table 4 Classification of Land Suitability for Rubber Plantation (Hardjowigeno et al., 1999)

Land Qualities

Land Suitability Classification

S1 S2 S3 N

Temperature

(ºC) 26-30

>30-34

24-<26 22-<24 Td

Rainfall

(mm/year) 2500-3000

>3000-3500 2000-<2500

3500-4000

1500-<2000 Td

Soil Texture SL, L, SCL, _{SiL, CL, Si,} SiCL

LS, SC,

SiC, C Str C Td

Slope

(%) <8 8-15 >15-25 >25-45

Soil Drainage well drained

Moderately Well, Somewhat poorly drained Somewhat excessively drained Poorly drained, excessively drained Elevation (asl)

<200 200-450 _{>450-600 >600}

Note: Td = Inoperative S = Sand Str C = Structured Clay

Si = Dust L = Clay

14

2.4 Geographical Information System

Geographic Information System (GIS) is a computer-based system used to store and manipulate geographic information. It is designed for collection, storage, and analysis of objects and phenomena where geographic location is an important characteristic or critical to the analysis (Aronoff, 1991). GIS is defined as an information system that is used to input, store, retrieve, manipulate, analyze and output geographically referenced data or geospatial data, in order to support decision making for planning and management of land use, natural resources, environment, transportation, urban facilities, and other administrative records. A computer system for GIS consists of hardware, software and procedure designed to support the data capture, processing, analysis, modeling and display of geospatial data (Murai, 1996).

Geographic information can be represented with geometric information such as location, shape and distribution, and attribute information such as characteristics and nature. Vectors and raster forms are the major representation models for geometric information. Most objects on a map can be represented as a combination of a point (or node), edge (or arc) and area (or polygon), which are vector forms. A point is represented by geographic coordinates. An edge is represented by a series of line segments with a start point and an end point. A polygon is defined as the sequential edges of a boundary. The inter-relationship between points, edges, and areas is called a topological relationship.

In the raster form, the object space is divided into a group of regularly spaced grids (pixels) to which the attributes are assigned. The raster form is basically identical to the data format of remote sensing data (Jars, 1993).

GIS can be a very important tool in decision making for sustainable development, because GIS can provide decision makers with useful information by means of analysis and assessment of spatial database. Decision making including policy making, planning and management can be interactively implemented taking into consideration human driving forces through public.

15

Driving forces include population growth, health and wealth, technology, politics, economics etc. by which human society will set up targets and goals on how to improve the quality of life (Bregt, 1997).

2.5 Multi Criteria Decision Analysis (MCDA)

Multi Criteria Decision Analysis (MCDA) or could be defined as MCDM (Multi Criteria Decision Making) techniques have largely been a spatial, but they are different in GIS context. Spatial MCDA which is applied in GIS requires both data on criterion values and the geographical locations of alternatives (Malczewski, 1999).

The main concept combination between MCDA and GIS is to support the decision maker in achieving greater effectiveness and efficiency. Some techniques used to support MCDA in decision making by using decision rules, to choose the best or the most preferred alternatives (Malczewski, 1999).

. The main method in weighted linear combination (WLC) assigns relative weight to each attribute. Decision maker directly assigns weights to each attributes. The highest overall score is chosen for the alternative. The weighted linear combination formula is as follows:

Wt = _Σi Wi.Xi ……Wn.Xn (1) Where; Wt = Total Weight

Wi = Weight value in each parameter i to n

Xn = Score value in each parameter i to n

2.6 Spatial Multi Criteria Analysis

Spatial Multi Criteria Decision Making (MCDM) is a process where geographical data is combined and transformed into a decision. In case the spatial MCDM, geographic data were used as input to the decision making. Spatial MCDM is more complex and difficult in contrast to conventional MCDM, as large numbers of factors need to be identified and considered, with high correlated relationships among the factors (Malzewski, 1999).

16

GIS have capability to store and analyze spatial data effectively, and it could be spatial modeling to support decision analysis (Center for GIS, 2005). GIS has long experience in decision making and map design, and it can integrate with MCDA system to support decision makers (Zhao and Garner, 2009).

The goal of spatial MCDM is to achieve solutions for spatial decision problems that take the input from multiple criteria. These criteria, also called attribute have to be identified very carefully to ensure that the final goal could be achieved (Prakash, 2003 in Dewi, 2008).

Spatial data analysis is in many ways the most important part of Geography Information System (GIS), because it includes all of the transformations, manipulations, and methods that can be applied to geographic data to add value to them, to support decision, and to reveal patterns and anomalies that are not immediately obvious. It is desirable that the geographical data management and analysis component contain a robust set of tools that are available in full fledged GIS system (Malczewski, 1999).

Method of analysis used MCDA approach for priority development area of rubber plantation criteria which is integrated with GIS. Assigning weighted value for criteria use Weighted Linear Combination (WLC) as described in equation 1 and Pair-wise Comparison Method (PCM).

2.7 Analytical Hierarchy Process (AHP)

Analytical Hierarchy Process (AHP) is a decision making approach developed by Saaty in 1980. The principles utilized in AHP to solve problems are to construct hierarchies. The hierarchy allows for the assessment of the contribution individual criterion at lower levels to make criterion at higher levels of the hierarchy.

The decision making in AHP is a process that continuous from analyzing the decision environment to understand and arrange the criteria into different groups and levels that reach the evaluation of the criteria in its decision outputs (Saaty, 1980). The AHP includes procedures and principles used to synthesize the

17

many judgments to derive priorities among criteria and down to alternative solution. AHP has several basic steps to be employed as follows (Saaty, 1980):

1. identify the problem and determine the goal, 2. structure the hierarchy from the top,

3. construct a set of pair wise comparison matrices,

4. there are n(n-1)/2 judgments required to develop each matrix in step 3, 5. determined the consistency using the Eigen value,

6. horizontal processing, 7. vertical processing,

8. Calculate the consistency ratio.

The AHP has three basic steps for considering decision problems by AHP. It begins by decomposing the overall goal (suitability) into a number of criteria and sub-criteria. The goal itself represents the top level of the hierarchy. Major criteria comprise two level, sub-criteria make up level three, and so on.

Each land mapping unit is an area which has common land-use characteristics. Sustainable evaluation of development area requires evaluate not only natural physical conditions but also socio-economic conditions. In order to determine which criteria (and at what levels or weights) affect development for each land-use type, experts are consulted to provide judgments on important of criteria. Using AHP technique these judgments on importance of criteria are converted to criteria weights (w

i). Score for each criterion (xi) on each land mapping unit is then determined. The weighted linear combination of w

i and xi give suitability index for each land mapping unit. By the above process, development area for rubber plantation map is produced.

18

The largest Eigen value is equal to the size of comparison matrix, or . Then calculate a measure of consistency, called Consistency Index as deviation or degree of consistency using the following formula.

(2)

After knowing the Consistency Index, the next question is how do we use this index? Prof. Saaty proposed that we use this index by comparing it with the appropriate one. The appropriate Consistency index is called Random Consistency Index (RI). The random consistency index should be 10% or less, random consistency index of sample size 500 matrices is used. The average random consistency index of sample size 500 matrices is shown in the Table 5.

Table 5 Random Consistency Index (RI)

n 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49

Some experiences in AHP process, the values of the pair wise comparison matrix will normally be well considered and not set arbitrarily. However, people’s feeling and preferences remain inconsistent and intransitive and may then lead to perturbations in the eigenvector calculations (Marinoni, 2004). Saaty (1986) defined a consistency ratio (CR) as a ratio of the consistency index CI to an average consistency index RI, thus;

(3)

RI or resulting average consistency index, also called the random index, was calculated by Saaty (1986) as the average consistency of square matrices of various orders n which he filled with random entries.

The consistency ratio (CR) should be about 10% or less to be acceptable. If the CR does not fall in the required range, the quality of the judgments should be improved.

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2.8 Rating (Absolute Measurement)

Duarte Junior (2005) defines ratings as a set of intensity levels (or categories) that serves as a base to evaluate the performance of the alternatives in terms of each criteria and/or sub criteria. The categories that form the ratings must be clearly defined, in the less ambiguous way as possible, to adequately describe the criterion/sub criteria. The rating is considered suitable as the decision makers consider it an appropriate tool to evaluate alternatives.

Figure 8 shows the hierarchy structure from the rating mode. The hierarchy begins with the global objective. The criteria are at the second level. The categories associated to the sub criteria are at the last level. The structure with ratings differs from the traditional AHP (relative measurement), because in the last level the alternatives are not found. The evaluation is performed by intensity levels (categories) attributed to each sub criteria related to each alternative, instead of evaluating the alternatives by pair wise comparisons.

The main advantage of using ratings is to decrease the number of comparisons necessary when there are a large number of alternatives. Besides, when using absolute measurement (ratings), it does not matter how many new alternatives are introduced, or old ones are excluded because there is no inversion of the alternatives ranking. In this research AHP application with ratings use the software Expert Choice version 9.50A05.

2.9 Supervised Classification

A classification describes the systematic framework with the names of the classes and the criteria used to distinguish them, and the relation between classes. In image classification there are two classification technique kinds that commonly known, supervised classification and unsupervised classification involves a training step followed by classification step. In the unsupervised approach the image data are first classified by aggregating them into natural grouping or clusters present in the scene (Lillesand and Kiefer, 1987).

20

In supervised classification this is realized by a operator who defines the spectral characteristics of the classes by identifying simple areas (training areas). Supervised classification requires that the operator be familiar with areas of interest. The operator needs to know where to find the classes of interest in the area covered by the image. This information can be derived from general area knowledge or from dedicated field observations (Janssen and Goerte, 2000).

Supervised classification is the procedure most often used for quantitative analysis of remote sensing image data. It rests upon using suitable algorithm to label the pixels in an image as representing particular ground cover types, or classes. A variety of algorithms is available for this, ranging from those based upon probability distribution models for the classes of interest to those in which the multi spectral space in partitioned into class-specific using optimally located sutface (Richards, 1993).

21

III. METHODOLOGY

3.1 Time and Location

This research was conducted from February to July 2011 that consisted of data collection, data analysis, method development, and model analysis. The data were collected from some government agencies such as meteorology, climatology, and geophysics agencies (BMKG) and rainfall gauges station near to the study area. The data analysis, method development and model analysis were accomplished at Bogor Agricultural University.

The study area is located in Banyuasin Regency, South Sumatra, Indonesia, which covers an area of 11,832.99 Km2 or about 12.18 % of South Sumatra Province and consists of 15 (fifteen) sub regencies. Banyuasin Regency is located between 10 18’ 00” and 40 00’ 00” South and 1040 40’ 00” and 1050 15’ 00” East (Figure 3), with the regency boundaries as follows: Northern part: Muara Jambi Regency, Jambi Province and Bangka Strait, Eastern part: The Air Sugihan of Ogan Komering Ilir Regency, Western - part: The Sei Lilin Sub Regency, Lais, Bayung Lencir of Musi Banyuasin regency, Southside: Abut The Sira Pulao Padang Sub Regency of Ogan Komering Ilir; Gulumbang Sub Regency, Talang Ubi Sub Regency of Muara Enim Regency.

22

3.2 Data and Tools 3.2.1 Supporting Data

The data used in the study consisted of remotely sensed data, topographic data, soil data and climate data. The tools are software required for image processing, spatial preparation process and spatial analysis as shown in Table 6.

Table 6 Supporting Data Required

No Datasets Data Format Resources Process

1. Climate Data: Daily rainfall (1989-2009) Daily Temperature (1989-2009)

Tabular BMKG in Jakarta Mapping and overlay

2. Soil Data: Soil Texture (1:250.000) Soil Drainage (1:250.000)

Shape file, Arc Info, or Hard copy

Balai Besar Sumber Daya Lahan

Pertanian

overlay

3. Topographic Map Scale 1:250.000

Shape file, Arc Info, or Hard copy

Bakosurtanal and Bappeda Banyuasin Regency

overlay

4. Land Use and Land Cover Map (2010) Scale 1:250.000

Land Use Map

Bakosurtanal and Bappeda Banyuasin Regency

overlay

5. Production Data: Rubber Palm oil Food Crops (corn,

soybean, peanut, green peal, cassava ,yam and oil palm)

Tabular Balai Penelitian Karet, Dinas Kehutanan dan Perkebunan, Dinas Tanaman Pangan Banyuasin Regency Mapping and overlay Analysis Multi Criteria

6. Social Data: Rubber area

Amount of rubber farmer

Tabular Badan Pelaksana Penyuluhan

Banyuasin Regency

Analysis Multi Criteria

7. Economy Data: Income of rubber and non rubber Cost of rubber and non rubber

Tabular Tree Crop Estate Statistics of Indonesia

Analysis Multi Criteria

8. Spot Imagery Bappeda Banyuasin

Regency

Classification of Plantation

23

3.2.2 Hardware and Software

Some instruments and software were used to support the field data recording and data analysis process. The hardware and software needed are shown in Table 7.

Table 7 Hardware and Software

No. Hardware/Software Specification Function 1. Hand held GPS receiver Garmin 76 CSX Positioning 2. Camera digital Pocket Camera Digital Documentation 3. Mobile Computer Acer Notebook with Intel

Core 2 Duo 2.1 GHz, 4 Gigabytes of Ram

Processing Unit

4. Color Printer Hp Deskjet F2276 Hardcopy

5. ArcGis Version 9.2 Spatial Data

analysis

6. ArcView Version 3.3 Spatial Data

analysis

7. ER Mapper Version 7.0 Classification of Plantation

8. Expert Choice version 9.50A05 AHP analysis

3.3 Methods

Prior to GIS data analysis, data preparation was done. Spatial data were generated based on UTM (Universal Transverse Mercator) coordinate system Zone 48 South and WGS 84 datum. The main stages carried out in this study were as follows: (1) analysis of Land Suitability for rubber plantation; (2) rubber production analysis; (3) Multi Criteria Analysis. Figure 4 shows the methodology flow chart of this research.

3.3.1 Land Suitability Analysis for Rubber Plantation

Land suitability analysis is to estimate the environment condition in order to determine plant types that are suitable to be planted on a given area. Generally, factors that can be considered for land suitability analysis are soil, slope, climate, and water availability.

24 N

Y

Non Suitable & Rubber, low Prod

Suitable & Rubber, low Prod Suitable &

Rubber, high Prod Non Suitable &

Rubber, high Prod

Retained Change with other

Commodity

Retained Developed & Management

Production

Priority Development of Rubber Plantation

Shrub ?

Developed Multi

Criteria Analysis

Spatial Analyze

Overlay

Productivity of rubber

Non Suitable and Non Rubber (Excluded)

Suitable and Rubber

Suitable and Non Rubber Non Suitable and Rubber

Land Suitability for Rubber Plantation

Existing Rubber of Land Use

Overlay

Spatial Data _{Tabular Data}

Data base

25

Land suitability analysis is intended to determine suitable land for cultivating specific crops or other utilization relating to agricultural activities (FAO, 1976 in Hananto, 2007).

This analysis based on is on the suitability of growing to plants the physical condition of environment consisting of soil, climate and topographic data/maps. Climate data consist of annual rainfall, number of dry months and number of wet months. Air temperature was derived from weather stations. Soil data considered in the land characteristic include soil drainage and soil texture. Topographic data consist of contour and processed to derive slope classes. The aim of this analysis is to determine land suitability for rubber plantation. To assess the overall suitability, a scoring and weighting system is applied to the various aspects of suitability are as follows:

o Rainfall data generated from monthly average precipitation data which has been collected and averaged from many years.

o Temperature data were generated such as rainfall data.

o Slope data for topography information derived from DEM of elevation data using contour line shape format.

o Soil texture and soil drainage data as physical soil characteristic information. In this study, every criterion was considered as they have an equal importance and has been given the same score in the scoring procedure, a score was assigned as shown in Table 8 depends on the input factor value.

Table 8 Structure of Suitability Classification

Categories Class Score Suitability Class S1

S2 S3 N

1 2 3 4

Highly Suitability Moderately Suitability Marginally Suitability Not Suitability

The scoring procedure was done for each factor so that there were 6 scores altogether. The total score was calculated by doing a sum all scores.

26

Total score = [rainfall score] + [temperature score] + [soil texture score] + [soil drainage score] + [elevation score] + [slope score] The suitability grade was calculated by averaging the total scores.

Total score

Suitability grade =

6

Table 9 Relations between Suitability Grades and Classes

Suitability Grade Suitability Class S = 1

1 < S <=2 2< S <= 3 3 < S <= 4

Highly Suitability Moderately Suitability Marginally Suitability Not Suitability

In agriculture, the land is highly suitable for all factors then it can be assumed that it is highly suitable for rubber plantation. But if there is one or more factors not highly suitable, then it cannot be considered as highly suitable. In this case, if the suitability grade (S) is equal to 1, then it is assigned as highly suitable (S1) because the requirement for every factor is highly suitable. The suitability site classification steps are described in Flowchart shown in Figure 5.

Figure 5 Flowchart of Land Suitability for Rubber Plantation Climate

Rainfall Temperature

Land Suitabilityfor Rubber Plantation

Overlay Suitability

Climate Map Soil Map Topographic Map

Overlay Overlay Overlay

Soil

Soil Texture Soil Drainage

Topography

Elevation Slope

27

3.3.2 Analysis of Existing Land Use Types

An inventory of existing land use was conducted using current land use and verified by field observation. Existing land uses were classified and the extent of their acreage determined as depicted Figure 6. The result of existing of land use analysis is used to the next analysis i.e., existing of rubber analysis.

In Figure 6, eight dominant existing land use types are identified: mixed gardens (136,666 ha), settlements (38,533 ha), mangrove forest (122,212 ha), plantation (105,927 ha), shrub (351,588 ha), paddy field (198,472 ha), swamp (11,346 ha) and bare land (26,573 ha). Map of land use in Banyuasin Regency please see Figure 6.

Based on the observation, it is known that mixed gardens could support annual income; mangrove forest could supports soil erosion control; plantation provide rural employment and export commodities and soil erosion control; paddy

field support annual income and food availability; bare land supports food availability for livestock. Therefore, these land utilization types were selected as

proposed land use types to solve environmental and economic problems in the area. In Figure 7, shrub cover an area of 351,588 ha which should be developed.

28 Figure 7 Land Use Map of Banyuasin Regency

3.3.3 Existing of Rubber Plantation

The Spot image was classified using Supervised Classification technique into several types of plantations. The classification processed was completed by land use data, areas statistic data, which obtained from the Banyuasin local government.

In supervised classification the process was validated by defining the spectral characteristics of the classes by identifying simple areas (training areas). After that, all vector data required were extracted using spatial processing software. The existing of rubber plantation data resulting will be used for the next spatial processing.

3.3.4 Productivity of Rubber Analysis

The main aim of this analysis is to evaluate condition of productivity of rubber in 2009. Land suitability and existing of rubber analysis produced four conditions. The first condition is ‘not suitable but not planted with rubber’, the second condition is ‘not suitable but planted with rubber’, the third condition is

29 ‘suitable but planted with rubber’ and the last condition is ‘suitable but not planted with rubber’.

The first condition will be excluded, but the second and the third condition were overlaid with productivity of rubber in 2009. The results of this overlay if high productivity value can retained to keep planted with rubber but for low productivity value can recommended to keep plant with rubber until produce wood, after that to change planted with other crops which suitable with characteristic of land suitability or develop rubber plantation along with production management.

The land suitable but not planted with rubber or the fourth condition was spatially analyzed with existing shrub, then to shrub areas was analyzed using multi criteria analysis using Analytical Hierarchy Process (AHP) to determine area priority to be developed as rubber plantation in sub regencies of Banyuasin Regency.

3.3.5 Multi Criteria Analysis

This research aimed at applying the Analytic Hierarchy Process (AHP) with ratings method to select area development of rubber in sub regency of Banyuasin Regency. Using ratings means categorizing previously defined criteria and/or sub-criteria in study to classify alternatives.

All criteria/factors, which are considered relevant for a decision, are compared against each other in a pair-wise comparison matrix which is a measure to express the relative preference among the factors. Therefore numerical values expressing a judgment of the relative importance (or preference) of one factor against another have to be assigned to each factor. Since it is known from psychological studies that an individual cannot simultaneously compare more than 7 ± 2 elements, Saaty (1977) and Saaty & Vargas (1991) suggested a scale for comparison consisting of values ranging from 1 to 9 which describe the intensity of importance (preference/dominance). A value of 1 expresses “equal importance” and a value of 9 are given for those factors having an “extreme importance” over another factor (Table 10).

30 Table 10 Scale and Definition of Pair-wise Comparisons

(Saaty and Vargas, 1991) No Intensity of

Importance Definition

1 1 Equal Importance

2 3 Moderate importance of one factor over another 3 5 Strong or essential importance

4 7 Very strong importance

5 9 Extreme importance

6 2.4.6.8 Intermediate value between the two adjacent _judgments

7

Reciprocals of above non-zero

numbers

If an activity has one of the above numbers (e.g. 3) compared with a second activity, then the second activity has the reciprocal value (i.e., 1/3) then compared to the first

Applying this step to development area analysis, decision criteria relevant to our goal were identified and arranged in the hierarchy illustrated in Figure 8.

Within each level of the hierarchy, the relative importance between each pair of criteria (or among pairs of sub-criteria relating to an upper single criterion) to the overall goal is evaluated. A nine-point scale is used for these evaluations. The third and final step in the AHP requires evaluation of the pair-wise comparison matrices using measurement theory. A standardized eigenvector is

Priority Development of Rubber Plantation

Socia l Economy

• Rubber Area • Number of rubber

Fa rmer Goal

Crit eria

• Ra tio of income of rubber with non rubber

• Ra tio of cost of rubber with non rubber Sub-crit eria

Figure 8 Rela tionship a mong goal, criteria, sub-criteria a nd a lternatives in AHP.

Alt ernat ives

Sub Regency B

31 extracted from each comparison matrix, allowing us to assign weights to criteria and sub-criteria. In this research, the decision matrix is formed to obtain the value of importance of the criteria, sub criteria and ratings. These values attribute are based on Saaty Fundamental Scale (Saaty, 1980). For each decision, the Consistency Ratio (CR) is calculated.

When dealing with multidiscipline expert with various judgments, it is important to check one by one of those consistencies of judgments. The selected result that has good consistency should be merged into one value. To merge the values of expert judgment, geometric mean method can be used (Marimin, 2008 in Nugroho, 2010). Pair wise comparison matrix process will use the result of geometric average method. The result of the completed questionnaire distributed to experts as main input data to calculate matrix.

The ratings with AHP method considered social and economic factors. This analysis has a purpose to determine priorities of sub regency for rubber development. Social factor used several variables such as area of rubber and number of rubber farmer. Economic factor used also two variables i.e. ratio income of rubber with non rubber and ratio cost of rubber with non rubber.

In rating models, each variable should be categorized into several classes (4 – 5 classes). This classes show the conditions of each variables (such as highly suitable, moderately suitable, marginally suitable and not suitable). For number of rubber farmer was classified into very high number of farmers (vhn), high number of farmers (hn), moderate number of farmers (mn), small number of farmers (sn) and very small number of farmer (vsn). This variable is indicated rubber is socially accepted if the number of rubber farmer is greater. For Area of rubber was claaified into very large, large, medium, small and very small. This variable is indicated rubber is socially accepted if the area of rubber is greater. Then for ratio income of rubber with non rubber was classified into very high, high, medium, low and very low. This variable is indicated rubber is economically accepted if the income of rubber is greater and for ratio cost of rubber with non rubber was classified into very large, large, moderate, small and very small. This variable is indicated rubber is economically accepted if the cost of rubber is smaller (please see Appendix 5).

53 2. The accurate data is needed to get more accurate information on land

suitability, productivity of rubber, social and economy data.

3. Information about land suitability area can be used by local government as a tool for land use planning, and for investors or farmers to determine which areas could are suitable to be planted with rubber trees.

4. Talang Kelapa Sub Regency and Rambutan Sub Regency are areas suitable for rubber plant but low productivity. There needs to be further research related to recommendation clone, use high quality seed for this sub regency. 5. Economic and social factors is vast and complex for it is necessary for

further research related to economic and social factors with respect to the character of each sub regency.

EVALUATION OF R GEOGRA

(Case Stu

BOGOR

OF RUBBER PLANTATION DEVELOPMENT OGRAPHIC INFORMATION SYSTEM AND

MULTI CRITERIA ANALYSIS

Study in Banyuasin Regency, South Sumatera)

MARTINI YULIA

GRADUATE SCHOOL

GOR AGRICULTURAL UNIVERSITY BOGOR

2011

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