Conclusions Recommendation CONCLUSIONS AND RECOMMENDATIONS
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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