Penerapan K-Means Clustering Untuk Menentukan Jumlah Pengangguran Berdasarkan Umur
Studi Kasus Di Badan Statistik Provinsi DKI Jakarta 2020-2022
DOI:
https://doi.org/10.62951/repeater.v2i3.116Keywords:
K-Means, unemployment, statisticsAbstract
Unemployment is a persistent problem in the labor market, thus hampering economic development and national prosperity. Indonesia, including its capital Jakarta, continues to face significant levels of unemployment compared to neighboring countries. This research focuses on analyzing the structure of unemployment in Jakarta using K-Means Clustering to categorize unemployment data based on age groups (2020-2022) sourced from the Central Statistics Agency. Analysis carried out via RapidMiner revealed three clusters:-Cluster 0: Age 30-60 years and above, Cluster 1: Age 20-24 years, Cluster 2: Age 15-19 and 25-29 years. The findings show that the 20-24 year age group has the highest unemployment rate (399,167 people), while the 30-60 year and above age group shows the lowest unemployment rate (75,560 people). This clustering approach provides insight into the distribution of unemployment by different age demographics in Jakarta, highlighting areas where targeted interventions may be needed to effectively address this socio-economic challenge
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