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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi
Citrawani Marthabakti
Department of Mathematics, Universitas Airlangga
Mathematics

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Analysis of Geographically Weighted Logistic Regression Models with A Bisquare Weighting Matrix on Poverty Status in West Java Toha Saifudin; Nur Chamidah; Najwa Khoir Aldawiyah; Citrawani Marthabakti; Aulia Ramadhanti; Muhammad Hafidzuddin Nahar; Naufal Muzakki
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36315

Abstract

This research addresses the first Sustainable Development Goal and aims to analyze poverty status in West Java Province, which has the second highest number of poor people in Indonesia. The study employs Geographically Weighted Logistic Regression (GWLR) and compares it with global logistic regression. Influential variables include GDP, unemployment, population density, access to safe water, and roof type (bamboo/wood). Results show that 55.6% of regions are classified as poor, with the GWLR model using a Fixed Bisquare kernel achieving 81.4% accuracy, outperforming global logistic regression at 66.7%. Significant variables vary by region: unemployment rate in Bogor, Depok, and Bekasi; population density in Bekasi, Karawang, and Purwakarta; water access in Sukabumi; and roof type in Indramayu and Bogor. These spatial variations suggest that poverty reduction requires a region-specific approach. Consequently, policies should be formulated considering the priorities and characteristics of each region in West Java Province.
Co-Authors Aulia Ramadhanti Muhammad Hafidzuddin Nahar Najwa Khoir Aldawiyah Naufal Muzakki Nur Chamidah Toha Saifudin