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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Bulletin of Computer Science Research
Roza, Yesi Betriana
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Computer Science & IT Economics, Econometrics & Finance Education Social Sciences

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Journal : Bulletin of Computer Science Research

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Analisis Cluster Algoritma K-Means Untuk Pengelompokan Kondisi Gizi Balita Pada Posyandu Roza, Yesi Betriana; Defit, Sarjon; Arlis, Syafri
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.752

Abstract

Toddler health is a crucial indicator of community and national development. Integrated Service Posts (Posyandu) play a key role in monitoring the nutritional status of toddlers through routine weight and height checks. This study aims to analyze toddler nutritional status using the K-Means Clustering algorithm, a non-hierarchical method that groups data based on centroid proximity. The data came from 98 toddlers at the Posyandu in Manggung Village, North Pariaman District, Pariaman City, including weight, height, weight-for-age, height-for-age, weight-for-height, and weight gain. The K-Means results showed a distribution of three clusters: C0 (undernourished) with 37 toddlers, C1 (severely malnourished) with 17 toddlers, and C2 (well-nourished) with 44 toddlers. The majority of toddlers were categorized as well-nourished. This research contributes to the rapid identification of toddler nutritional problems, enabling Posyandu staff to take appropriate preventive and corrective measures.
Co-Authors Erlanda, Hadrian Nurdiansyah, Ali Sarjon Defit Sovia, Rini Syafri Arlis Syafril Syafril