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Abstract

West Java was the province with the highest unemployed rate during the COVID-19 pandemic. Significant increase of open ‎unemployment rate in West Java negatively impacts the national income. This study aims to apply the ‎clustering method using the k-means algorithm to determine priority clusters in West Java ‎Province by looking at the number of clusters in West Java’s city and the main characteristic of ‎each cluster. The clustering was conducted utilizing a k-means clustering algorithm which is grouping data based on similar ‎characteristics. The clustering results were evaluated using silhouette method. The results indicated that ‎two clusters were optimal. The clustering process using the k-means method showed that there were three clusters distinguishing the open unemployment rate during the pandemic in West Java Province in 2020. Cluster 1 ‎had a fairly low open unemployment rate due to the stalled service sector and low minimum city wage. ‎Cluster 2 had a high open unemployment rate due to the service sector and high minimum city wage. ‎Cluster 3 had medium open unemployment rate due to the service sector and also medium minimum city ‎wage. It suggests that cluster 2 is a priority cluster in dealing with the open unemployment rate.‎

Keywords

k-means clustering open unemployment West Java Province

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How to Cite
Ardiansyah, M. F. H., Amany, N., Anugrah, C. I., & Syafitri, U. D. (2024). K-Means Clustering Application of Open ‎Unemployment in 2020 Caused by COVID-19 in West Java Province. Enthusiastic : International Journal of Applied Statistics and Data Science, 4(1), 1–12. https://doi.org/10.20885/enthusiastic.vol4.iss1.art1
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