Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers

  • Melissa Indah Fianty Universitas Multimedia Nusantara, Indonesia
  • Monika Evelin Johan Universitas Multimedia Nusantara, Indonesia
  • Azka Aulia Universitas Multimedia Nusantara, Indonesia
  • Mella Margareta Veronica Universitas Multimedia Nusantara, Indonesia
DOI: 10.51519/journalisi.v5i4.586
Keywords: Data mining, K-means Clustering, Malnutrition, Nutritional Status, Toddlers

Abstract

Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia.

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Published
2023-12-02
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How to Cite
Fianty, M., Johan, M., Aulia, A., & Veronica, M. (2023). Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers. Journal of Information Systems and Informatics, 5(4), 1350-1362. https://doi.org/10.51519/journalisi.v5i4.586
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Vol 5 No 4 (2023): Journal of Information Systems and Informatics
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Articles

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