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All Journal SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Samsinar
Universitas Sulawesi Barat

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Integration of Local Moran's I and Geographically Weighted Regression for Early Detection of Potential Stunting Crisis Areas: A Case Study of South Sulawesi Province Reski Wahyu Yanti; Nurul Azizah Muzakir; Arwini Arisandi; Samsinar
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol. 15 No. 1 (2026): Volume 15 Nomor 1 (Maret 2026)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/c9asjt27

Abstract

Stunting is a chronic nutritional problem that has long-term impacts on physical growth, cognitive development, and the quality of human resources. South Sulawesi Province still faces a high prevalence of stunting with variations in conditions between districts/cities. This study aims to conduct early detection of areas with potential stunting crises through the integration of Local Moran's I spatial analysis and the Geographically Weighted Regression (GWR) method. The research data consists of secondary data from the Statistics Indonesia (BPS) in 2024 in 24 districts/cities with variables related to nutritional, socioeconomic, and environmental factors. The analysis stage begins with OLS regression and classical assumption tests, followed by the Local Moran's I test to identify spatial autocorrelation patterns, indicating clustering of at-risk areas. Therefore, GWR modeling is used to map variations in the influence of local determinants of stunting. The results show that the GWR model outperforms OLS based on increased R² values ​​and coefficient variations between regions, with significant variable differences in each location. These findings emphasize the importance of region-specific stunting management policies as a basis for early detection and more effective intervention in South Sulawesi Province.
Co-Authors Arwini Arisandi Nurul Azizah Muzakir Reski Wahyu Yanti