Faktor-faktor Penentu Kemiskinan Di Indonesia: Analisis Rumah Tangga

The purpose of this study is to provide an overview of poverty in Indonesia by mapping the provinces based on economic growth and poverty rate as well as knowing the determinants of poverty in Indonesia with analysis at household level. The analysis used secondary data from Indonesia's Central Bureau of Statistic and Susenas (National Sosioeconomic Survey) in March 2012. Based on poverty mapping, the provinces are divided to four quadrant and the analysis on 2007 and 2012 show quadrant position change of some provinces. There are provinces that getting better, those are Central Java and Maluku while North Sumatera, Banten, West Kalimantan, South Kalimantan, and South Sumatera show the worse condition. Analysis determinants of poverty measures probability of a household to be poor using logit regression model find that household characteristics likes sex of household head, age of household head, number of household member, employment status of household head, access to credit, education of household head, access of information and communication technology, and locational (rural/urban) significantly affect the poor status of household in Indonesia

Dampak Remitansi Tenaga Kerja Indonesia Terhadap Distribusi Pendapatan Rumah Tangga : Analisis Sistem Neraca Sosial Ekonomi Indonesia (SNSE) 2008

This study aims to analyze the impact of Indonesian workers' remittances on income distribution of households, in which includes the total impact as well as the details of the road from the impact. The data used is the Social Accounting Matrix (SAM) of Indonesia in 2008. The methodology used is matrix multiplier balance with Leontief inverse analysis and details of the impact analyzed through decomposition of the matrix multiplier. The results of this study showed that the group of households that are affected most by the injection of remittances in the government sector is domestic agricultural entrepreneurs while the total impact on the production sector to get the most impact is the sector of Real Estate and Business Services sector, followed by trade

Pengaruh Faktor Sosial Ekonomi terhadap Angka Kematian Bayi (AKB) pada Kabupaten/Kota di Propinsi Jawa Timur

Infant Mortality Rate (IMR) is one indicator of health development. IMR of East Java Province showed its success in reducing IMR, but if considered in each regency in East Java province was still among the high, in addition there were still 21 municipal regencies that still exceeded the 2014-2019 RPJMD target of East Java Province. This study tries to analyze the socioeconomic factors of the Infant Mortality Rate in East Java Province. This study uses a panel data regression, using panel data 38 city districts in East Java. This study uses independent variables: PDRB per capita, Mean Years School of Women, length of time supporting breastfeeding, percentage of households that require up to 30 minutes, number of posyandu, number of medical personnel, number of paramedics and immunization. The results of the regression test showed that the overall variable was the infant mortality rate in East Java Province, but only the variables gave breastfeeding and the number of medical workers who did not match the infant mortality rate in East Java Province

Profil dan Determinan Kerentanan Kemiskinan Rumah Tangga

Concept of vulnerability to poverty appears by a presence of shocks as an important dimension of poverty. The existence of shocks lead to insecurity in household welfare. This measurement of vulnerability to poverty is trying to measure probability of households fall in to poverty in the future. This study aims to measure household vulnerability to poverty and examine its determinants on the basis of a household survey data for Indonesia. Sampel data used is secondary data from IFLS 5 (Indonesia Family Life Survey) year 2014. The measurement of vulnerability to poverty is analyzed using three stage FGLS (Feasible Generalized Least Square), while its determinant is analyzed using logit regression methods. Results of this study show that Lampung province, DKI Jakarta, Sumatera Utara, Sumatera Barat, Kalimantan Selatan, dan Nusa Tenggara Barat have a high average value of vulnerability to poverty. Moreover, Lampung Province is the most vulnerable in 2014. Furthermore, this study find that age of household head, education of household head, household size,location, saving ownership,and land ownership have a significant effect on household value of vulnerability to poverty