Thobias Melemabessy
Lelemuku Saumlaki University, Saumlaki, Indonesia

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Classification of villages in Tanimbar Islands based on stunting service packages using the K-Means Algorithm Mesak Ratuanik; Samuel Urath; Pesparani Diana Jabar; Baceria Werluka; Inda A. Batbual; Thobias Melemabessy
Cendikia : Media Jurnal Ilmiah Pendidikan Vol 14 No 5 (2024): May: Education Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cendikia.v14i5.4947

Abstract

The Tanimbar Islands Regency still has a high prevalence of stunting in toddlers, so we must work together to eradicate it. According to WHO, the prevalence of stunting should not exceed 20%. According to data from the 2021 Indonesian Nutritional Status Survey (SSGI), the prevalence of stunting in toddlers is currently 25.1% in the Tanimbar Islands District, Maluku Province. The purpose of this study was to classify villages based on the indicators of the stunting service package in the Tanimbar Islands District. This research uses an analytic survey approach using secondary data obtained from the Central Bureau of Statistics (BPS) of the Republic of Indonesia in 2022 and the Tanimbar Islands District Health Office in 2022 by utilizing the K-Means Algorithm. The stages of data analysis in this study consisted of library research, data collection, data processing, the K-Means algorithm. Furthermore, the last stage is to verify the data consisting of analysis of findings based on the theory used. At this analysis stage, the K-Means Clustering Method was also applied to classify villages in the Tanimbar Islands District based on the stunting service package. Research results based on analysis using the K-Means algorithm (Number of causes in each cluster) provide an overview of the number of clusters that enter each cluster. Cluster 1 consists of 20 villages, cluster 2 consists of 66 villages, cluster 3 consists of 1 village and cluster 4 consists of 1 village.