Implementation of the X-Means Algorithm on Unemployment Data in West Java

Abstract

The unemployment rate is a serious issue in many countries, including Indonesia, with impacts that encompass psychological pressure, declining living standards, reduced national income, and diminished workforce quality. High unemployment rates can lead to poverty, resource wastage, and have implications for a country's economic growth. Additionally, inadequate workforce quality is a determining factor in unemployment rates. The objective of this study is to classify unemployment data, specifically in West Java Province, using the X-Means algorithm based on educational levels and districts/cities, in order to examine the fluctuations in unemployment. The research findings indicate fluctuations in the number of unemployed individuals in West Java Province from 2011 to 2022. The low unemployment rate in West Java Province experienced a 66.7% increase in 2014-2015, remained stable in 2017-2019, while the high unemployment rate decreased by 80% in 2014-2015, remained stable in 2017-2019, but increased by 20% in 2020-2022. Furthermore, Bogor Regency consistently recorded the highest unemployment rate in each cluster, with a total of 135,000 unemployed individuals in Bogor Regency in 2017-2019, while the education level with the highest unemployment rate was junior high school graduates