Application of the Mean-Shift Method in Grouping the Influence of Labor Market Information on Labor Absorption in West Java Province
DOI:
https://doi.org/10.47709/brilliance.v5i1.5920Keywords:
Mean-Shift, Labor Absorption, West Java Province, Spayial Clustering, Silhoutte ScoreAbstract
The imbalance between the number of job seekers and the availability of jobs is a challenge in the labor market in West Java Province. This study aims to group districts/cities based on the influence of labor market information on labor absorption using the Mean-Shift algorithm. Data were obtained from BPS for the 2019–2023 period, covering the number of job seekers, vacancies, and job placements. Data were processed through cleaning, transformation, normalization, and aggregation of a five-year average. Clustering was carried out using the Mean-Shift algorithm with an optimal bandwidth of 0.474611, resulting in two clusters with a Silhouette Score of 0.4943. The first cluster consists of areas with low labor absorption rates, characterized by the number of job seekers that are not comparable to vacancies and job placements. The second cluster includes areas with higher and more balanced labor absorption. The results of the study show that the Mean-Shift algorithm is able to group regions based on labor market characteristics. These findings suggest that labor market information can be used to map regions based on labor absorption rates in a more targeted manner, as well as support the formulation of data-based employment policies.
References
Adil, R. A., Naukoko, A. T., Wauran, P. C., Pembangunan, J. E., Ekonomi, F., & Bisnis, D. (2019). ANALISIS DAMPAK SEKTOR PARIWISATA TERHADAP PENDAPATAN ASLI DAERAH DAN PENYERAPAN TENAGA KERJA.
Agustin, E. (2020). PENGARUH TINGKAT PENDIDIKAN DAN UMK TERHADAP PENYERAPAN TENAGA KERJA DI KABUPATEN MOJOKERTO TAHUN 2014-2018.
Ali Akbar, B., & Adhari Shandi, A. (2021). PENGEMBANGAN SISTEM INFORMASI PASAR KERJA STUDI KASUS?: DINAS TENAGA KERJA DAN TRANSMIGRASI KABUPATEN SUBANG. VII(2).
Ananda Yudhatama, F., Imanta Ginting, R., Studi Sistem Informasi, P., & Triguna Dharma, S. (2024). Pengelompokan Pelatihan Tenaga Kerja Berdasarkan Data Pelamar Kerja Menggunakan Metode K-Means. 3, 411. https://ojs.trigunadharma.ac.id/index.php/jsi
An-Naziz Safaat, W., Kurniawan, R., & Wijaya, Y. A. (2024). PENERAPAN DATA MINING CLUSTERING MENGGUNAKAN ALGORITMA FUZZY C-MEANS PADA DATA PENCARI KERJA DI KABUPATEN KUNINGAN. In Jurnal Mahasiswa Teknik Informatika (Vol. 8, Issue 2). http://karirhub.kemnaker.go.id./
Ayu, D., Dewi, I. C., & Pramita, K. (2019). Analisis Perbandingan Metode Elbow dan Sillhouette pada Algoritma Clustering K-Medoids dalam Pengelompokan Produksi Kerajinan Bali. In JURNAL MATRIX (Vol. 9, Issue 3).
Ayuningtyas, I., Suryanata, M., Pusat, B., Provinsi, S., & Timur, K. (2022). Pengelompokan Provinsi di Indonesia Menurut Indikator Pasar Tenaga Kerja (Clustering of Provinces in Indonesia According to Key Indicators of Labour Market).
Cariou, C., Le Moan, S., & Chehdi, K. (2022). A Novel Mean-Shift Algorithm for Data Clustering. IEEE Access, 10, 14575–14585. https://doi.org/10.1109/ACCESS.2022.3147951
Chen, J., Yang, J., Huang, J., & Liu, Y. (2021). Robust truth discovery scheme based on mean shift clustering algorithm. Journal of Internet Technology, 22(4), 835–842. https://doi.org/10.53106/160792642021072204011
Cinderatama, T. A., Zulmy Alhamri, R., Yunhasnawa, Y., Polinema, P., Kediri, K., Maskumambang, J. L., Mojoroto, K., Informasi, J. T., Malang, N., Soekarno Hatta, J., Lowokwaru, K., & Malang, K. (2022). Implementasi Metode K-Means, Dbscan, dan Meanshift Untuk Analisis Jenis Ancaman Jaringan Pada Intrusion Detection System. 7(1), 2022.
Hani, S. R. (2023). CLUSTERING DATA PENCARI KERJA MENURUT TINGKAT PENDIDIKAN MENGGUNAKAN ALGORITMA K-MEANS. Jurnal Minfo Polgan, 12(1), 1–14. https://doi.org/10.33395/jmp.v12i1.12217
Karolina, N. (2021). Data Mining Pengelompokan Pasien Rawat Inap Peserta BPJS Menggunakan Metode Clustering (Studi Kasus?: RSU.Bangkatan). In JOURNAL OF INFORMATION AND TECHNOLOGY UNIMOR. www.kaputama.ac.id
Rizuan, R., Haerani, E., Jasril, J., & Oktavia, L. (2023). Penerapan Algoritma Mean-Shift Pada Clustering Penerimaan Bantuan Pangan Non Tunai. Journal of Computer System and Informatics (JoSYC), 4(4), 1019–1027. https://doi.org/10.47065/josyc.v4i4.3876
Setiyawan, B. , A. I. , & H. A. D. (2018). Analisis dan Perancangan Sistem Informasi Pelayanan Informasi Pasar (Vol. 2, Issue 9). http://j-ptiik.ub.ac.id
Susilowati, D., & Wicaksono, Y. (2024). Penerapan Data Mining Untuk Clustering Data Pencari Kerja dengan Menggunakan Algoritma K-Means. Pseudocode, 11(2), 54–58. https://doi.org/10.33369/pseudocode.11.2.54-58
Yamasaki, R., & Tanaka, T. (n.d.). IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (PRE-PRINT VERSION) 1 Properties of Mean Shift.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Khaerani Ulfah, Fitrah Rumaisa
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
info@itscience.org, web: 
