Penerapan geographically weighted regression (GWR) dalam menganalisis kemiskinan di Pulau Jawa tahun 2022
(Utilizing geographically weighted regression (GWR) for poverty analysis on Java Island in 2022)
Embedded Files
Jeremia Novaldi
Politeknik Statistika STIS, Jakarta
Novi Hidayat Pusponegoro
Politeknik Statistika STIS, Jakarta
DOI: https://doi.org/10.19184/mims.v24i1.42717
ABSTRACT
Poverty is a priority issue for Indonesia. However, efforts to eradicate poverty in Indonesia have always failed to fulfill the targets set out in the RPJMN. Java Island, which is known as the center of the economy, has not yet solved this poverty problem. In 2022, the majority of provinces on Java Island still have a higher poverty rate than the target in the 2020-2024 RPJMN, which is 6.5-7 percent. Therefore, the objective of this study is to analyze the relationship between the socio-economic conditions of the society, represented by aspects of education, health, and income, and poverty in 119 regencies or cities on Java Island. Geographically weighted regression (GWR) with a fixed bi-square kernel is applied to fulfill the study objective. The results showed that poverty is affected by RLS in 84 districts/cities, influenced by AHH in 15 regencies or cities, and influenced by AHH and income per capita in 8 regencies or cities. However, these three variables do not affect the poverty rate in the 12 regencies or cities.
Keywords: Poverty, GWR, spatial analysis, socioeconomic.
MSC2020: 91B72
Published
15-03-2024
Issue
Vol. 24 No. 1 2024: Majalah Ilmiah Matematika dan Statistika
Pages
61-72
License
Copyright (c) 2024 Majalah Ilmiah Matematika dan Statistika
Page updated
Report abuse