Source of Data METHODOLOGY

III. METHODOLOGY

3.1. Source of Data

The source of data that used in this research were National Social Economic Survey Susenas 2005, data analyzed by Insan Hitawasana Sejahtera IHS on the percentage of job seekers 2005, and Potensi Desa Podes 2005 conducted by CBS. The data used for hotspot detection consisted of household monthly consumption per capita used for poverty hotspot detection, proportion of unemployment per municipality used for unemployment hotspot detection and household total daily calorie intake used for food scarcity hotspot detection for 111 municipalities 78 districts and 33 cities in Java, Indonesia. There were several definitions on Poverty made by the NGOs and GoI Institutions. This research used a widely definition based on Central Bureau of Statistics CBS. A household is categorized as poor if they have an income per capita below the poverty line. The poverty line is a measure of the amount of money a government or a society believes is necessary for a person to live at a minimum level of subsistence or standard of living. For food security, Ariani 2006 referred that World Bank since 1986 categorized food insecurity into chronic food insecurity and transitoryoccasional food insecurity. This research focused on chronic food insecurity, where there is a condition of frequent food scarcity over a certain period of time. On a household level, chronic food insecurity indicates that the share of food owned is slight lower than needed. A household is considered to be food scarce if the total daily calorie intake is lower than 70 of the minimum calorie needed ±1400 kcal. Meanwhile unemployment occur when a person is available to work and seeking work but currently without work. The prevalence of unemployment is usually measured using the proportion of unemployment, which in this study was defined as the percentage of those in the labour force who are unemployed and aged 14-24 y.o. The explanatory variables that used for ordinal logistic regression were from Podes. The 12 variables used were chosen from a wide variety of 23 variables that were not correlated and assumed to have a significant influence on poverty, unemployment, and food scarcity hotspots. These variables were related to citizenship and labour, education and health, transportation, communication and information, economy, politics and security, housing and environment sectors, and also location. The variable and their specific sector can be seen in Table 2. Table 2 List Of Explanatory Variables Per District And Its Sector No Variable Sector Note 1. Economy Potentials of a Village: Farming, Industry, Trade, ServicesOthers Economy Ratio of Potential VillagesVillages in a Municipality 2. The amount of farmers Citizenship and Labour Ratio of FarmersVillages in a Municipality 3. The amount of farm labourers Citizenship and Labour Ratio of Farm LaboursVillages in a Municipality 4. The average amount of education facilities Education and Health Ratio of SchoolVillages in a Municipality 5. The average distance between the village to the capital statecity Location Km 6. The amount of small and medium scale industries Economy Ratio of industryVillages in a Municipality 7. Credit facilities Economy Ratio of CreditVillages in a Municipality 8. The presence of conflicts within the society Politics and Security Ratio of Conflicts recorded Villages in a Municipality 9. The average amount of families without electricity PLN Housing and Environment Ratio of FamiliesVillages in a Municipality 10. Province Location Dummy Variable Banten, West Java, Jakarta, Central Java, Yogyakarta, and East Java 11. Slum areas Housing and Environment Ratio of Slum AreasVillages in a Municipality 12. Indonesian Labour Force Citizenship and Labour Ratio of PeopleVillages in a Municipality

3.2. Method