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Berliana, Sarni Marniar
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Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Pemodelan Geographically Weighted Panel Regression (GWPR) pada Rumah Tangga yang Menempati Rumah Kumuh di Indonesia Tahun 2020—2022 Ninda, Faradilla Chairin; Dinayanti, Lisma; Berliana, Sarni Marniar
Seminar Nasional Official Statistics Vol 2024 No 1 (2024): Seminar Nasional Official Statistics 2024
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/semnasoffstat.v2024i1.2028

Abstract

Slum housing is a global problem, and it's on the 11th goal of the Sustainable Development Goals (SDGs). In Indonesia, the percentage of households occupying slum houses decreased significantly between 2020 and 2022. The average annual decrease is only 7.7%, down from 12.58% in 2019. The Theory of Slums and the Culture of Poverty concept definitively states that the emergence of slums is caused by social and economic characteristics. However, it is clear that spatial characteristics also influence slum housing due to its dispersed pattern. The regional autonomy policy also plays a role in regulating slum houses. To address these issues, we employ a method that can overcome spatial heterogeneity in panel data: Geographically Weighted Panel Regression (GWPR). The inferential analysis yielded 23 groups based on variables with significant influence. The predictor variables were open unemployment rate, life expectancy, average years of schooling, population growth rate, population density, proportion of informal employment, and percentage of poor people.
Co-Authors Dinayanti, Lisma Ninda, Faradilla Chairin