Analysis of the Poverty Level Model for West Sumatra Province Using Geographically Weighted Binary Logistic Regression

Abstract

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West Sumatra Province (West Sumatra) ranks third lowest in terms of the poverty rate on the island of Sumatra in 2022, with a figure of 5.92%. Although this figure is lower than the national average, the Province of West Sumatra is targeting a reduction in the poverty rate to 5.62% in 2024 in the vision of the 2021–2026 Regional Development Plan. The purpose of this study is to analyze the factors that contribute to the poverty rate in West Sumatra Province based on geography in 2022. The method used to address poverty problems is Geographically Weighted Binary Logistic Regression (GWBLR), which takes geographical influences into account in the analysis. This study uses data on the percentage of poor people (Y) and the influencing factors, namely life expectancy (X1), literacy rate (X2), labor force participation (X3), and economic growth (X4). The results showed that based on the lowest Akaike Information Criterion Corrected (AICc) value, the GWBLR model with a Fixed Gaussian Kernel weight is the best at modeling the problem of poverty in West Sumatra in 2022. According to the model, the life expectancy variable will have a significant impact on the level of poverty in 13 districts and cities in West Sumatra Province in 2022.