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Implementasi Density-Based Spatial Clustering of Applications With Noise Dalam Pengelompokan Wilayah Ketahanan Pangan Papua Maruruk, Aginda Ersita; Situmeang, Radian J.; Aryanto, Aryanto
Journal of Health, Education, Economics, Science, and Technology Vol. 7 No. 2 (2025): Journal of Health, Education, Economics, Science, and Technology
Publisher : Journal of Health, Education, Economics, Science, and Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/

Abstract

The province of Papua has a food security index (FSI) of 42.27% in 2023. This figure is lower than other provinces in Indonesia, which is influenced by indicators from the aspects of food availability, physical and economic accessibility of food, and food utilization. Grouping regions based on their characteristics and conditions will help the government identify priority areas for policy interventions aimed at improving food security in those regions. This study aims to group districts/cities based on the FSI using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) approach and analyze the food security conditions of each district/city in Papua Province in 2023. The results of this study identified three main clusters and two noise areas with a silhouette coefficient of 0.4434. Cluster 0 is classified as Moderately Food Secure and Prosperous, cluster 1 is classified as Highly Food Insecure & Socially Vulnerable, and cluster 2 is classified as Food Insecure with Good Access to Water. The two noise regions have unique characteristics: Keerom Regency is a Transition Toward Food Security region, and Puncak Regency is a region with deviations in both social and economic characteristics. This indicates that the DBSCAN method is effective in identifying spatial food security characteristics in Papua and can be used as a basis for more targeted food security policy planning.