Analisis Penentuan Karyawan Tetap Dengan Algoritma K-Means Dan Davies Bouldin Index

  • Bobby Kristanto * Mail Universitas Pelita Bangsa, Indonesia
  • Ahmad Turmudi Zy Pelita Bangsa, Bekasi, Indonesia
  • M. Fatchan Pelita Bangsa, Bekasi, Indonesia

Abstract

Developments Technological advances are things that cannot be avoided in this life because technological developments go hand in hand with advances in science. With the rapid development of technology today, of course it affects the work environment as well. Employees are one of the company's reasons for determining the continuity of business activities. Employee work contracts within the company are important and must be considered in order to achieve company goals. PT. Taewon Indonesia is engaged in paper production and has more than 300 contract workers, making it difficult to select or expel workers who are still suitable and meet the requirements of the contract extension process. Analysis of determining permanent employees is very important for companies to determine recruitment strategies and human resource development. This study analyzes the determination of permanent workers using two clustering algorithms, K-Means and Davies Bouldin Index. K-Means is used to collect employee data based on certain criteria, while the Davies Bouldin Index is used to measure the quality of clustering results. Of the 455 employee performance appraisal datasets, tests were carried out by determining 2 clusters and validation was tested with the Davies Bouldin Index. And the resulting -1.752. Based on the results obtained, it shows that the k-means algorithm can be implemented in clusters to determine permanent workers with fairly good validation results

References

J. Pembangunan, P. : Fondasi, D. Aplikasi, M. Ngafifi, S. Negeri, and S. Wonosobo, “Kemajuan Teknologi dan Pola Hidup Manusia ... Muhamad Ngafifi 33 KEMAJUAN TEKNOLOGI DAN POLA HIDUP MANUSIA DALAM PERSPEKTIF SOSIAL BUDAYA.” [Online]. Available: http://www.tempo.co/read/news/2010/12/23

M. A. Ghufron, “Seminar Nasional dan Diskusi Panel Multidisiplin Hasil Penelitian & Pengabdian kepada Masyarakat, Jakarta, 2 Agustus 2018 REVOLUSI INDUSTRI 4.0: TANTANGAN, PELUANG DAN SOLUSI BAGI DUNIA PENDIDIKAN.”

S. K. D. Agustin Rozalena, PANDUAN PRAKTIS MENYUSUN DAN PELATIHAN KARYAWAN PENGEMBANGAN KARIER. 2016.

W. N. Wk, M. Kom, and F. da Cintia, “IMPLEMENTASI DATA MINING UNTUK PREDIKSI STATUS KONTRAK KERJA KARYAWAN MENGGUNAKAN ALGORITMA NAIVE BAYES STUDI KASUS KOSPIN JASA,” 2018.

F. Priyono et al., “PERBANDINGAN TEKNIK KLASIFIKASI UNTUK PREDIKSI STATUS KONTRAK KERJA KARYAWAN.”

Y. S. Wicaksono, “PENGARUH PELATIHAN DAN PENGEMBANGAN SUMBER DAYA MANUSIA DALAM RANGKA MENINGKATKAN SEMANGAT KERJA DAN KINERJA KARYAWAN (Studi di SKM Unit V PT. Gudang Garam,Tbk Kediri).”

W. Julianto, R. Yunitarini, and M. K. Sophan, “ALGORITMA C4.5 UNTUK PENILAIAN KINERJA KARYAWAN”.

D. Transaksi Bongkar Muat di Provinsi Riau, I. Kamila, U. Khairunnisa, P. Studi Sistem Informasi, and F. Sains dan Teknologi UIN Sultan Syarif Kasim Riau, “Perbandingan Algoritma K-Means dan K-Medoids untuk Pengelompokan,” Jurnal Ilmiah Rekayasa dan Manajemen Sistem Informasi, vol. 5, no. 1, pp. 119–125, 2019.

B. Setiani, “KAJIAN SUMBER DAYA MANUSIA DALAM PROSES REKRUTMEN TENAGA KERJA DI PERUSAHAAN.”

D. D. Darmansah and N. W. Wardani, “Analisis Pesebaran Penularan Virus Corona di Provinsi Jawa Tengah Menggunakan Metode K-Means Clustering,” JATISI (Jurnal Teknik Informatika dan Sistem Informasi), vol. 8, no. 1, pp. 105–117, Mar. 2021, doi: 10.35957/jatisi.v8i1.590.

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Published
2023-03-27
How to Cite
Kristanto, B., Turmudi Zy, A., & M. Fatchan. (2023). Analisis Penentuan Karyawan Tetap Dengan Algoritma K-Means Dan Davies Bouldin Index. Bulletin of Information Technology (BIT), 4(1), 112 - 120. https://doi.org/10.47065/bit.v4i1.521
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Articles