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Journal : EKSAKTA: Journal of Sciences and Data Analysis

K-Means ++ Algorithm for Health Services Clustering Based on Districts in West Java Province Nur, Indah Manfaati; Abdurakhman
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 1, April 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss1.art11

Abstract

A healthy and prosperous life is one of the goal points listed in the Sustainable Development Goals (SDGs). To create a healthy life, support is needed in the form of equal health facilities and services for all people in all provinces of Indonesia. In fact, there are still provinces that have low levels of health service facilities. West Java is ranked last with low health service conditions. Grouping efforts are needed to identify cities or districts in West Java that deserve priority for handling health facilities. In this study, the K-Means++ method was used to group health facilities based on cities or districts in West Java Province. Based on the grouping results, 3 clusters were obtained, namely cluster 1 for groups with low health facilities with 18 cities/regencies as members, cluster 2 for groups with moderate health facilities with 7 cities/regencies, and cluster 3 for groups with high health facilities with 2 cities/regencies