Identification of adaptation activities from the government that

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Chapter 5 VULNERABILITY AND ADAPTIVE

CAPACITY MAPPING

5.1 Methodology for Vulnerability and Adaptive Capacity

Mapping For defining capacity and vulnerability indices, we used 2005 socio-economic survey data by ‘kelurahan’ villages from National Bureau of Statistics BPS while for some of biophysical data were obtained from related sector or generated based on satellite interpretation with GIS techniques Table 5.1. All the data were weighted according to their relative importance in shaping vulnerability V and capacity C to adapt. Table 5.1:..Indicators used for defining Vulnerability and Capacity and the corresponding weights A Capacity Weights B Vulnerability Weights A1 Electricity Facility 0.05 B1 Number of household living in River Bank 0.05 A2 Working People based on Education Background 0.30 B2 Number of Building in River Bank 0.05 A21 Nursery –Junior High School 0.30 B3 Drinking Water 0.20 A24 Senior High SchoolUniv. 0.70 B31 Good 0.10 A3 Main Source of Income 0.30 B32 Medium 0.20 A4 Health facility 0.10 B33 Bad 0.30 A41 Puskesmas 0.20 B34 No-service 0.40 A42 Polyclinic 0.30 B4 Population density 0.10 A43 Posyandu 0.20 B5 Poverty 0.20 A44 Midwifes Clinic 0.10 B6 Fraction of Coastal 0.10 A45 Med. Doctor Clinic 0.20 B7 Fraction of River 0.10 A5 Road Infrastructure 0.25 B8 Non-Green Open Area 0.20 Note: In term of facility, Polyclinic is better than Puskesmas as it is managed and operated by Private company, but the cost of health services is much higher than the government’s one Puskesmas. Data obtained from the Semarang Drinking Water State Company PDAM Office and divide by population. Data were generated from Satellite and topographic map. To measure relative position of Kelurahan in term of their vulnerability and capacity to adapt, we develop capacity CI and vulnerability indices VI. The Capacity Index CI is developed using five main indicators A1, …, A5. Indicator A1 is percentage of household in the village that uses electricity facility which represents the level of wealth of communities of the villages. Indicator A2 is education which may represent the capacity of community in the villages in managing the risk. The higher the education is the better their capacity in managing the risk is. This indicator consists of two sub-indicators namely number of working people with education background of Nursery up to junior high schools and that with Senior High 69 School up University. All the values of the sub-indicators were normalized by population of each Kelurahan. In order to get values of the indicators ranges from 0 to 1, all the values in this indicator were divided by its maximum value. Indicator A3 is main income source of community in the village. For villages where main source of income of the community is strongly influenced by climate variability will have low capacity score. The values of the indicator by main source of incomes are presented in Table 5.2. In this case for example, village in which agriculture is the main source of income of the community, the value of the indicator is 0.25. Table 5.2:..Indicator value according to types of main income source of community in the village No Main source of income Score Indicator value 1 Agriculture 0.25 2 Mining and processing industries 0.50 3 Trading, transportation and communication business etc 0.75 4 Services 1.00 Indicator A4 is health facility which represents access of community to health facilities. The better the health facility in the Kelurahan is the higher the capacity of the Kelurahan is. This indicator is further divided into 5 sub-indicators namely number of Polyclinic Pl, Child Community Services Posyandu, Ps, Health Community Services Puskesmas, Pk, Midwifes Clinic B and Doctor Clinics D. All the values of the sub-indicators were normalized by population size of the corresponding Kelurahan. The scoring value of I A4 in each Kelurahan was calculated using the following formula: I A4i = 1P i 0.3Pl i +0.2Ps i +0.2P ki +0.1B i + 0.2D i Since the scoring value of this indicator is very small, all the values were divided with the highest score in order to get scoring values of the indicator ranging from 0 to 1. Indicator 5 is dominant type of road infrastructure. For this data we define village where the dominant road infrastructure is made from aspalt will have value 1 while for those with non-aspalt will have value 0. The formula to calculate the CI is the following: ij ij j i A w CI 5 1 ∑ = = Where subscript-i th represents village-i th and w ij is weight value for indicator A-j th of village-i th . The selection of the weight values was subjective, based on understanding and knowledge of experts on relative important of the indicators in