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All Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Salsabilla, D O C
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Computer Science & IT

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Clustering of Cities/Regencies in East Java Province Based on the Number of Health Workers Using K-Means Clustering Analysis Nashir, Farras Ijlal; Safitri, N R; Salsabilla, D O C
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.710

Abstract

This study aims to classify cities/regencies in East Java Province based on the availability of health workers using the K-Means clustering analysis method. Secondary data was obtained from BPS East Java for the year 2024, covering 12 variables of health worker types. The analysis process included data standardization, determination of the optimal number of clusters using the Silhouette method, and the application of the K-Means algorithm. The analysis results show that the optimal number of clusters is two. Cluster 1 exclusively consists of the City of Surabaya, characterized by a high concentration of modern and technical health workers but lower in community-based health workers. Cluster 2 includes the other 37 cities/regencies, showing a greater dependence on basic health workers such as midwives and nutritionists, with limited access to specialist medical personnel. This study recommends strengthening community health workers in Surabaya and increasing the availability of professional medical personnel in other regions to reduce health service disparities in East Java.
Co-Authors Nashir, Farras Ijlal Safitri, N R