Analysis of Malnutrition Status in Toddlers Using the K-MEANS Algorithm Case Study in DKI Jakarta Province

Authors

  • Ita Dewi Sintawati Universitas Bina Sarana Informatika, Indonesia
  • Widiarina Universitas Bina Sarana Informatika, Indonesia
  • Kartika Mariskhana Universitas Bina Sarana Informatika

DOI:

10.33395/sinkron.v8i4.14087

Keywords:

Malnutrition in toddlers, K-Means, DKI Jakarta, and prevalence

Abstract

Malnutrition in children is a serious health issue in various regions, including DKI Jakarta Province, which affects the physical and cognitive development of children. This research aims to classify malnutrition status in children using the K-Means algorithm, focusing on cases in DKI Jakarta. The objective is to identify patterns of malnutrition prevalence across different regions, serving as a basis for more effective interventions. The data used in this study includes the percentage of children with severely stunted, stunted, and normal nutritional status across six districts/cities in DKI Jakarta. The results of K-Means clustering show that Central Jakarta has the highest prevalence of severely stunted (10.50%) and stunted (13.01%) status, while West Jakarta has the lowest prevalence of severely stunted (4.62%) and stunted (10.22%) status. The solution offered by this research is the grouping of regions based on malnutrition prevalence, allowing for the identification of areas requiring priority intervention. The analysis results indicate that DKI Jakarta can be classified into several clusters based on malnutrition prevalence. The cluster with the highest malnutrition prevalence includes Central Jakarta, while the cluster with the lowest malnutrition prevalence includes West Jakarta and the Thousand Islands. The implementation of K-Means in this research provides an efficient approach to identifying groups of regions that need more attention in combating malnutrition in children. In conclusion, this research can serve as an important reference for policymakers in formulating more effective and efficient intervention strategies in DKI Jakarta, as well as inspire similar studies in other regions with different population characteristics

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How to Cite

Sintawati, I. D. ., Widiarina, W., & Mariskhana, K. (2024). Analysis of Malnutrition Status in Toddlers Using the K-MEANS Algorithm Case Study in DKI Jakarta Province. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 8(4), 2318-2324. https://doi.org/10.33395/sinkron.v8i4.14087

Issue

Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024

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Articles

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Copyright (c) 2024 Ita Dewi Sintawati, Widiarina, Kartika Mariskhana

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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