Klasterisasi Status Stunting pada Balita Menggunakan Algoritma K-Means
DOI:
https://doi.org/10.29408/jit.v9i2.35298Keywords:
K-Means Algorithm, Toddler, Clustering, StuntingAbstract
Stunting is a growth and development disorder in children due to chronic malnutrition and repeated infections characterized by below-standard height. Cadres conduct monthly Posyandu data collection by weighing and measuring toddlers. However, the Posyandu data results only become piles of paper in the cadres' homes. Based on these conditions, it is necessary to process data for clustering that can help the village government in grouping toddler data so that the government knows the number of stunted and normal toddlers, which can later be used as evaluation material in the future in taking action to reduce, prevent and overcome stunting cases. This study aims to group stunted and normal toddlers based on age, weight, and height variables. The method applied is data clustering using the K-Means Algorithm. The results of this study are clusters divided into 2 clusters, in cluster 1 there are 406 toddlers with normal status as many as 119 toddlers and toddlers with stunting status as many as 287 toddlers, while in cluster 2 there are 326 toddlers with normal status as many as 52 toddlers and toddlers with stunting status as many as 274 toddlers. A total of 171 toddlers with normal status, representing 23.4%, and 561 toddlers with stunting, representing 76.6%. These results demonstrate the critical need for support from integrated health posts (Posyandu) and relevant community health centers (Puskesmas) to parents of toddlers to reduce or even eliminate stunting in the following period.
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