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Dewi Andini Putri
Universitas Royal Asahan Sumatera Utara

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Stunting Risk Cluster Analysis In Petatal Plantation Village Using K-Means Clustering Approach Dewi Andini Putri; Dewi Maharani; Ahmad Muhazir
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): In Progress
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.299

Abstract

Stunting is a chronic nutritional issue that requires accurate, data-driven intervention. This study aims to map the level of stunting risk among toddlers in Perkebunan Petatal Village by categorizing them into high, medium, and low-risk groups. The research method employed is descriptive quantitative, utilizing the K-Means Clustering algorithm to group toddler data based on related risk indicators. The analysis results revealed three risk clusters: Cluster 1 (high risk) consisting of 14 toddler data, Cluster 2 (medium risk) consisting of 17 toddler data, and Cluster 3 (low risk) consisting of 19 toddler data. These findings indicate that while the majority of toddlers fall into the low-risk category, there are still toddlers in the high and medium-risk categories who require specific attention from village authorities and health workers. This information serves as a crucial basis for determining nutritional intervention priorities and designing more targeted and data-driven stunting prevention programs in Perkebunan Petatal Village
Co-Authors Ahmad Muhazir Dewi Maharani