https://jurnal.unipar.ac.id/index.php/estimator/issue/feed 2026-02-09T16:24:43+08:00 Dwi Agustin Retnowardani 2i.agustin@gmail.com Open Journal Systems <p><strong>ESTIMATOR: Journal of Applied Statistics, Mathematics, and Data Science</strong> is a journal managed by the Statistics Study Program, Faculty of Science and Technology, Universitas PGRI Argopuro Jember. This journal is published twice a year and covers research in the fields of statistics and its applications, data science, mathematics and its applications, and mathematics education.</p> https://jurnal.unipar.ac.id/index.php/estimator/article/view/2874 2025-12-13T09:16:57+08:00 Baharuddin baharuddin.mtmk@uho.ac.id

<p><em>Poverty in Indonesia exhibits significant spatial variation between regions, including on the island of Sulawesi, which possesses diverse geographic and economic characteristics. This study aims to analyze the inequality in poverty rates between regencies/cities in Sulawesi in 2025 and to identify the patterns of their spatial clustering. Using secondary data from Statistics Indonesia (BPS) for 2025 covering 81 regencies/cities, this research applies a spatial exploration approach through global spatial autocorrelation analysis (Moran's Index and Geary's Index) and local analysis (LISA). The results indicate high inequality between regency areas (average 10.48%) and city areas (average 5.31%). A significant positive global spatial autocorrelation was detected (Moran's Index = 0.25 and Geary's Index = 0.75), indicating that poverty tends to cluster geographically. LISA analysis identified High-High clusters in the central and southeastern regions (particularly Gorontalo Province, Central Sulawesi, and Southeast Sulawesi) and Low-Low clusters in urban areas and the northern part of the island. These findings underscore the importance of spatially-based and integrated poverty alleviation policies for priority cluster regions.</em></p>

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