Factors affecting poverty using a geographically weighted regression approach (case study of Java Island, 2020)

Abstract

Poverty is still the main problem in development both at the national and regional levels. The poverty reduction program carried out has not paid attention to spatial aspects so that the policies taken are often not on target. This study aims to see the spatial pattern of poverty in Java Island which includes Banten, DKI Jakarta, West Java, Central Java, DI Yogyakarta and East Java. The method used is geographically weighted regression (GWR) with addiptive weighting of the Gaussian Kernel which is processed with QGIS, Geoda and GWR4 software. This approach can identify spatial patterns that cannot be identified in ordinary regression analysis as found in previous studies. The data used in this study is secondary data in 2020 sourced from the Badan Pusat Statistik (BPS) and government website. The results of the study showed positive and group spatial autocorrelation in 34 districts/cities. There are 65 districts/cities in Java Island only affected by HDI, 4 districts/cities affected by TPT and HDI, 47 districts/cities affected by MSEs and HDI, and 3 districts/cities affected by TPT, UMK and HDI. The government can improve the quality of education, the level of public health services, and provide job training to reduce poverty.