đ
09 October 2023
DOI: 10.36499/jinrpl.v5i2.8736
Penerapan Algoritme K-Means Dalam Mengelompokkan Data Pengangguran Terbuka Di Provinsi Jawa Barat
Jurnal Informatika dan Rekayasa Perangkat Lunak
Universitas Wahid Hasyim
đ Abstract
Unemployment is a major social problem in many regions, including West Java province in Indonesia. West Java province is one of the most populous regions with a high level of urbanization. With population growth and urbanization, the challenge of creating enough jobs becomes more difficult. Therefore, the purpose of this study is to cluster open unemployment data in West Java communities classified by the number of unemployed people by district or city. This research uses CRISP-DM method with K-Means clustering algorithm. The result of this research is 10 regencies/cities that have low level of unemployment, then there are 15 regencies/cities that have medium level of unemployment and there are 2 regencies/cities that have high level of unemployment. The result of the test using Davies Bouldin Index cluster = 3 has the best cluster quality, because the value of the Davies Bouldin Index test result with c = 3 is the smallest value of 0.28, which is the lower, the better the cluster.
đ Keywords
#Clustering; Data Mining; Unemployment
âšī¸ Informasi Publikasi
Tanggal Publikasi
09 October 2023
Volume / Nomor / Tahun
Volume 5, Nomor 2, Tahun 2023
đ HOW TO CITE
Muthmainnah, Tasyifa Nafsiah; Indriyana, Siti; Enri, Ultach, "Penerapan Algoritme K-Means Dalam Mengelompokkan Data Pengangguran Terbuka Di Provinsi Jawa Barat," Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 5, no. 2, Oct. 2023.
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