Implementasi Metode K-Means Clustering dalam Mengukur Tingkat Gizi Balita Berdasarkan Z-Score

Toddler health is very important as the basis for child development. Every child must receive good nutrition so that their development stages are not disrupted. This study aims to analyze the nutritional status of toddlers at Posyandu Currently, Posyandu Parents are given a Healthy Way Card (KMS) where the card only contains the child's age and weight. The data used includes the age, weight and body length of 20 toddlers. The analysis process involves determining the Z-Score for each parameter to group the data into three main clusters, namely overnutrition, obesity and risk of overnutrition. The research results showed that of the 20 toddlers, 6 were in the obese category, 13 were over-nourished, and 1 toddler was at risk of over-nutrition. This information can be a basis for evaluation for parents and Posyandu in increasing appropriate nutritional intake for children.

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Journal
Building of Informatics Technology and Science (BITS)
Published
2024-12-25
DOI
https://doi.org/10.47065/bits.v6i3.6177
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Implementasi Metode K-Means Clustering dalam Mengukur Tingkat Gizi Balita Berdasarkan Z-Score

Mesran Mesran, Desyanti Desyanti, Welly Desriyati
Building of Informatics Technology and Science (BITS)
Data Mining and Machine Learning Applications
article

Implementasi Metode K-Means Clustering dalam Mengukur Tingkat Gizi Balita Berdasarkan Z-Score

Mesran Mesran, Desyanti Desyanti, Welly Desriyati
article en

Abstract

Toddler health is very important as the basis for child development. Every child must receive good nutrition so that their development stages are not disrupted. This study aims to analyze the nutritional status of toddlers at Posyandu Currently, Posyandu Parents are given a Healthy Way Card (KMS) where the card only contains the child's age and weight. The data used includes the age, weight and body length of 20 toddlers. The analysis process involves determining the Z-Score for each parameter to group the data into three main clusters, namely overnutrition, obesity and risk of overnutrition. The research results showed that of the 20 toddlers, 6 were in the obese category, 13 were over-nourished, and 1 toddler was at risk of over-nutrition. This information can be a basis for evaluation for parents and Posyandu in increasing appropriate nutritional intake for children.

Building of Informatics Technology and Science (BITS)Vol. 6(3)
Telkom Institute of Management (ID)
Openalex Percentile: Top 53%
Data Mining and Machine Learning Applications
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Implementasi Metode K-Means Clustering dalam Mengukur Tingkat Gizi Balita Berdasarkan Z-Score — Mesran Mesran, Desyanti Desyanti, et al. · Building of Informatics Technology and Science (BITS) (2024) | TGRS Research Map | TGRS