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Journal of Applied Statistics, Mathematics, and Data Science
Published by Universitas PGRI Argopuro Jember
ISSN : -     EISSN : 30218403     DOI : https://doi.org/10.31537/estimator.v1i1.1180
Core Subject : Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics
ESTIMATOR: Journal of Applied Statistics, Mathematics, and Data Science merupakan jurnal yang dikelola oleh Program Studi Statistika, Fakultas Sains dan Teknologi, Universitas PGRI Argopuro Jember. Jurnal ini akan terbit dua kali dalam setahun dengan ruang lingkup penelitian mengenai bidang kajian ilmu statistika dan terapannya, bidang ilmu data sains, bidang ilmu matematika dan terapannya, dan bidang ilmu pendidikan matematika.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 1 Documents
 1 
Search results for , issue "Vol. 3 No. 2 (2025): -" : 1 Documents clear
Eksplorasi Spasial Tingkat Kemiskinan di Pulau Sulawesi Tahun 2025 Baharuddin
ESTIMATOR : Journal of Applied Statistics, Mathematics, and Data Science Vol. 3 No. 2 (2025): -
Publisher : Program Studi Statistika Universitas PGRI Argopuro Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31537/estimator.v3i2.2874

Abstract

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.

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