Implementation of K-Means Cluster for Districts or Cities in West Java Province Based on Unemployment Indicators

Alifa Nur Oktaviani; Atika Nurani Ambarwati

doi:10.36456/jstat.vol18.no1.a10311

Authors

Alifa Nur Oktaviani Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang
Atika Nurani Ambarwati Institut Teknologi Statistika dan Bisnis Muhammadiyah Semarang

DOI:

https://doi.org/10.36456/jstat.vol18.no1.a10311

Keywords:

K-Means, West Java, Open Unemployment

Abstract

The high disparity of open unemployment rate among regions in West Java Province is an issue that requires mapping based on regional socioeconomic characteristics. The purpose of this study is to group districts/cities in West Java based on the open unemployment rate and its influencing factors using the K-Means Cluster method. The data used is secondary data for the year 2023 obtained from the Central Bureau of Statistics. Assumption test was conducted using KMO and Bartlett's Test to ensure sample adequacy and feasibility of data structure. The results of the analysis show that the regions in West Java are divided into three clusters. Cluster 1 consists of regions with high development but also high unemployment rates, such as Bandung City and Bekasi Regency. Cluster 2 includes regions with medium socioeconomic conditions, such as Depok City and Bandung Regency. Cluster 3 consists of regions with low development, low HDI, and high poverty, such as Ciamis, Garut, and Pangandaran. These findings indicate the existence of significant inequality among regions and can serve as a basis for the formulation of more targeted and region-based unemployment reduction policies.

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