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All Journal Repeater: Publikasi Teknik Informatika dan Jaringan
Dody Renal Syahputra
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Computer Science & IT

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Penerapan K-Means Clustering Untuk Menentukan Jumlah Pengangguran Berdasarkan Umur : Studi Kasus Di Badan Statistik Provinsi DKI Jakarta 2020-2022 Andi Diah Kuswanto; Azumardi Nabil Fadhila; Paulus Tri Setiawan; Muhammad Kevin Setiawan; Dody Renal Syahputra
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 2 No. 3 (2024): Juli : Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v2i3.116

Abstract

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
Co-Authors Andi Diah Kuswanto Azumardi Nabil Fadhila Muhammad Kevin Setiawan Paulus Tri Setiawan