Conclusions Recommendation CONCLUSIONS AND RECOMMENDATIONS

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Developing GIS Tools to Integrate MCDM for the Analysis of Bank Branch Closures. 6th International Conference on GeoComputation, Brisbane, Australia. Appendix 1: input Pairwise Comparison Matrix PCM of all criteria 1. Respondents 1 Criteria Rainfall Temperature Priority Rainfall 1 5 0.834 Temperature 15 1 0.166 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 7 3 0.686 Distance From River 17 1 1 0.135 Slope 13 1 1 0.179 CR = 0.0703 Criteria Distance road Distance factory Priority Distance road 1 13 0.25 Distance factory 3 1 0.75 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 5 7 0.723 Land condition 15 1 3 0.193 Accessibility 17 13 1 0.084 CR = 0.0568 2. Respondents 2 Criteria Rainfall Temperature Priority Rainfall 1 7 0.875 Temperature 17 1 0.125 CR= 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3 5 0.634 Distance From River 13 1 3 0.260 Slope 15 13 1 0.106 CR =0.03338 Criteria Distance road Distance factory Priority Distance road 1 15 0.167 Distance factory 5 1 0.833 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 1 7 0.510 Land condition 1 1 3 0.390 Accessibility 17 13 1 0.100 CR = 0.0697 3. Respondents 3 Criteria Rainfall Temperature Priority Rainfall 1 3 0.75 Temperature 13 1 0.25 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3 5 0.648 Distance From River 13 1 2 0.230 Slope 15 12 1 0.122 CR = 0.0318 Criteria Distance road Distance factory Priority Distance road 1 4 0.8 Distance factory 14 1 0.2 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 1 3 0.428 Land condition 1 1 3 0.428 Accessibility 13 13 1 0.144 CR = 0.000 4. Respondents 4 Criteria Rainfall Temperature Priority Rainfall 1 7 0.875 Temperature 17 1 0.125 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3 5 0.634 Distance From River 13 1 3 0.260 Slope 15 13 1 0.106 CR = 0.0333 Criteria Distance road Distance factory Priority Distance road 1 1 0.5 Distance factory 1 1 0.5 CR = 0.000 Criteria Climate Land Condition Accessibility Priority Climate 1 1 3 0.4054 Land condition 1 1 5 0.4796 Accessibility 13 15 1 0.1150 CR = 0.0251 5. Respondents 5 Criteria Rainfall Temperature Priority Rainfall 1 7 0.875 Temperature 17 1 0.125 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3 5 0.634 Distance From River 13 1 3 0.260 Slope 15 13 1 0.106 CR = 0.0333 Criteria Distance road Distance factory Priority Distance road 1 18 0.111 Distance factory 8 1 0.889 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 1 3 0.405 Land condition 1 1 5 0.480 Accessibility 13 15 1 0.115 CR = 0.0251 6. Respondents 6 Criteria Rainfall Temperature Priority Rainfall 1 8 0.889 Temperature 18 1 0.111 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3 5 0.619 Distance From River 13 1 4 0.284 Slope 15 14 1 0.097 CR = 0.0747 Criteria Distance road Distance factory Priority Distance road 1 4 0.8 Distance factory 14 1 0.2 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 3 7 0.668 Land condition 13 1 3 0.243 Accessibility 17 13 1 0.089 CR = 0.0060 Appendix 2: Geometric Mean of Input PCM for All Criteria Criteria Rainfall Temp Priority Rainfall 1 8.3 0.890 Temp 18.3 1 0.110 CR = 0.000 Criteria Soil Type Distance from River Slope Priority Soil Type 1 3.45 4.59 0.650 Distc From River 13.45 1 2.45 0.230 Slope 14.59 12.45 1 0.120 CR = 0.0360 Criteria Distance road Distance factory Priority Distance road 1 0.71 0.420 Distance factory 10.71 1 0.580 CR = 0.000 Criteria Climate Land condition Accessibility Priority Climate 1 1.57 4.58 0.530 Land condition 10.57 1 3.55 0.360 Accessibility 14.58 13.55 1 0.11 CR = 0.003 Appendix 3 : ILWIS Step in Spatial Multi-Criteria Evaluation SMCE ILWIS 3.4, 2010; http:spatial-analyst.netILWIShelp.html START Identification of the main Goal Identification of a hierarchy of sub goals Identification of criteria or effects, which measure the performance of the sub goals Creating and filling a criteria tree, which represents the hierarchy of the main goal, any sub goals, and the criteria. Assignment of input maps to criteria for each alternative Identification of alternatives to be evaluated Determination of a standardization method per criterion Weighing of criteria in the criteria tree Calculation of the Composite Index maps and visualization Inspecting the values in the Composite Index maps Classifying or slicing the Composite Index maps Calculation of Shape Index FINISH Appendix 4. Suitability map of oil palm plantation in Musi Banyuasin regency a Map of Musi Banyuasin Regency b Map of suitability oil palm and existing plantation in Musi Banyuasin regency c Map of development area oil palm plantation in Musi Banyuasin regency a Map of Musi Banyuasin regency 55 b Map of suitability oil palm and existing plantation in Musi Banyuasin regency c Map of development area oil palm plantation in Musi Banyuasin regency ABSTRACT YUDI ASTONI. Determining Oil Palm Plantation Potential Location Using Spatial Multi-Criteria Evaluation Case Study in Musi Banyuasin Regency, South Sumatra Province. Under the Supervision of SURIA DARMA TARIGAN and HARTANTO SANJAYA Indonesia has the potential land to grow oil palm plantation and currently being the largest producer of crude palm oil CPO. Satellite remote sensing data is very potential to be used in studies of forest conditions and plantation, because remote sensing data gives current and accurate information. Sumatra Island, especially Musi Banyuasin regency is one of area that has potential for oil palm plantation development. The objective of this research is to determine the potential location of oil palm plantation development by considering bio-physical criteria such as climate suitability, land condition, and accessibility in Musi Banyuasin regency, and to evaluate the suitability map of oil palm plantation that obtained compared with existing plantation in Musi Banyuasin regency. The Method of this research is based on multi criteria decision making by implementing GIS model technology using spatial multi criteria evaluation that will determine location of oil palm plantation potential. Each criterion and alternatives should be evaluated and weighted using pairwise comparison method to determine the best location for oil palm plantation potential in Musi Banyuasin Regency. Geographic Information System GIS analysis using Spatial Multi Criteria Evaluation SMCE in finding the best location for oil palm plantation succeeded to choose Sungai Lilin Sub-District as the best location for oil palm plantation development. Sungai Lilin Sub-District has the total suitability area of 62,246.37 Ha or 20.30 of Musi Banyuasin area. Based on the calculation area and percentage of suitability map and existing oil palm plantation indicated that area Highly Suitable S1 for development plantation area is 306,612.42 ha or 21.23 of Musi Banyuasin regency and for the existing plantation area is 223,699.66 ha or 15.49. Keyword: GIS, SMCE, oil palm plantation

I. INTRODUCTION

1.1 Background

A significant change in the oil palm industry has taken place during the past season, as Indonesia surpassed Malaysia in production of palm oil and is now the world leader. Indonesia has become the first largest world producer of crude palm oil CPO followed by Malaysia GAPKI, 2006. Together these two countries account for 84 of total world production and 88 of global exports Guerin, 2006. The demand for oil palm significantly increased both local and export, so that land clearing for plantation in Sumatra and Kalimantan regions expanded. Satellite remote sensing data is very potential to be used in studies of forest conditions and plantation, because remote sensing data gives current and accurate information. Sumatra Island, especially Musi Banyuasin regency is one of area that has potential for oil palm plantation development. Suitability for plant cultivation need to be considered in order to obtain optimal growth, although the plants seem to grow together in a region, but each type of plant has a character that requires different requirements, so that optimum production can be observed among the suitability of land for farming and growing requirements for each type of plant. Potential land for plantation development basically determined by the physical properties and the environment which include: soil, topography, hydrology and climate. Suitability between the physical properties with the requirements of the use of a commodity to be evaluated will give an idea or information that the land has potential for the development of these commodities. This means that if the land is used for a specific use by providing the necessary input it will give results as expected. Geographic Information System GIS is a powerful tool of acquisition, management and analysis of spatially-referenced data. With the combination of Multi-Criteria Analysis MCA, GIS provides a decision support tool that help decision making process. The use of GIS-MCA or commonly known as Spatial Multi-Criteria Evaluation SMCE in providing alternative locations of potential land for palm oil plantation will give decision maker the ability to choose the best location for plantation intensification from many criteria.

1.2 Problem Statement

Musi Banyuasin regency has large potential area for the development of oil palm plantations. With this condition, the main problem in this research is: where are optimal locations priority for oil palm development by considering the criteria for climate suitability, land condition, and accessibility using Geographic Information System GIS technology?”

1.3 Research Objectives

The objectives of this research are: 1. To determine the potential location of oil palm plantation development by considering bio physical criteria such as climate suitability, land condition, and accessibility in Musi Banyuasin regency. 2. To evaluate the generated suitability map of oil palm plantation with existing plantation in Musi Banyuasin regency.

1.4 Research Scope

This research is intended to search for the potential areas which can be exploited for oil palm plantation development in Musi Banyuasin regency. In this research, land suitability analysis for oil palm plantation development will be carried out using GIS with processing spatial data such as intersect and buffer processing for a few maps and Spatial Multi-Criteria Evaluation SMCE technique and used pairwise method as significant tool in decision making.

I. LITERATURE REVIEW

2.1 Geographic Information System

Geographic Information System GIS is a collection of tools, which can be used for conducting some procedures to collect, store, retrieve at will, transform, and display geographical data from the real world Burrough 1986. Functionally, GIS can be subdivided into four main components, namely: data input, data storage and management, data manipulation and analysis and data output Malczewski 1999. In GIS database, the major objects at conceptual level are geographic object. These objects relate to an entity in real word, which consist of two elements: spatial data and attribute data. The capability to process spatial data differentiates GIS and other kinds of database application. The spatial data is represented in form of points, lines, and polygons and is stored in one of two methods: raster and vector. The spatial data can be obtained either by field survey using GPS equipment Global Positioning System or by the result of satellite image interpretation.

2.2 GIS for Land Suitability Analysis

GIS has been used as a tool for developing alternative uses of agricultural land, precision farming, crop yield or land suitability mapping in determining the best alternative for agricultural production. The ability of GIS to integrate, display, and query many types of information at the same time makes it an important tool for decision support in agriculture. Information derived from remote sensing and GIS technologies are being effectively utilized in several areas for sustainable agricultural development and management. One of the most useful tools in GIS is its ability to form overlay operations between layers especially in selecting or locating suitable area for agricultural purposes. According to FAO 1976, suitability is a measure of how well the qualities of a land unit match the requirements of a particular form of land 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. De la Rosa 2000 stated that land suitability is a component of sustainable evaluation of land use. Suitability together with vulnerability defines the suitability of a land use. The sustainable land use should have maximum suitability and minimum vulnerability, as shown in Figure 1. Figure 1 Land use sustainability de la Rosa 2000 Land suitability analysis deals with information, which is measured in different scales like ordinal, nominal, ratio scale etc. Based on the scope of suitability there are two types of classifications in FAO 1976 framework.  Current suitability: refers to the suitability for a defined use of land in its present condition, without any major improvements in it.  Potential suitability: for a defined use, of land units in their condition at some future date, after specified major improvements have been completed where necessary. According to Malczewski 1999, spatial multi criteria decision analysis can be thought as a process that combines and transforms geographical data input into a resultant decision output. The critical aspect of spatial multi-criteria analysis that it involves evaluation of geographical event based on the criterion values and preferences set with respect to a set of evaluation criteria. The combination of GIS capabilities with Multi Criteria Decision Making MCDM technique provides greater effectiveness and efficiency of decision making while solving spatial decision problems.