Perbandingan Metode K-NN dan SVM Berdasarkan Kinerja Pegawai
DOI:
https://doi.org/10.30865/json.v4i3.5816Keywords:
Classification, K-NN, SVM, Comparison, PerformanceAbstract
Limited qualified human resources cause employees not to do the job in accordance with the company's operational standards properly and correctly. At this time PT. XYZ does not have tools to identify employee performance, therefore researchers conduct research to assist PT. XYZ in classifying employee performance. The methods used in this study were K-NN and SVM with a sample of 873 PT. XYZ employee data. Based on the trials conducted, the K-NN method has the highest accuracy rate of 90.13%, 91% precision rate, and 98.95% recall rate. The most optimal number of neighbors (k value) for the K-NN method is 5 with an accuracy rate of 88.35%.References
K. Hadi and B. N. Hidayah, “PENGARUH BEBAN KERJA, LINGKUNGAN KERJA DAN KOMPENSASI TERHADAP KINERJA KARYAWAN PADA PT. KALIMIAS BINTANG PRATAMA CABANG LOMBOK TENGAH,†VALID Jurnal Ilmiah, pp. 215–223, 2019.
A. Amellya, F. Fitriasuri, and E. Elpanso, “Pengaruh Kompetensi dan Motivasi terhadap Kinerja Pegawai pada Badan Pengelola Keuangan dan Aset Daerah Kabupaten Banyuasin,†2022.
Hasmin and J. Nurung, MANAJEMEN SUMBER DAYA MANUSIA, 2021st ed. 2021. doi: 10.31237/osf.io/yvpue.
B. HARALAYYA Hod and A. Professor, “Employee Performance Appraisal at Sri Veerabhadreshwar Motors Bidar,†2022.
A. S. Lombu, S. Hidayat, and A. F. Hidayatullah, “Pemodelan Klasifikasi Gaji Menggunakan Support Vector Machine,†Journal of Computer System and Informatics (JoSYC), vol. 3, no. 4, pp. 363–370, Sep. 2022, doi: 10.47065/josyc.v3i4.2137.
A. Rahmat, K. Auliasari, and Y. A. Pranoto, “IMPLEMENTASI METODE K-NEAREST NEIGHBOR (KNN) UNTUK SELEKSI CALON KARYAWAN BARU (Studi Kasus : BFI Finance Surabaya),†2020.
I. Setiari, “PENGARUH SISTEM IMBALAN DAN KEBIJAKAN UPAH TERHADAP PRESTASI KERJA PEGAWAI KANTOR DEPARTEMEN AGAMA KOTA BANJAR,†Jurnal Media Teknologi, vol. 09, no. 01, 2022.
R. Umar, I. Riadi, and Purwono, “Klasifikasi Kinerja Programmer pada Aktivitas Media Sosial dengan Metode Stochastic Gradient Descent,†JOINTECS (Journal of Information Technology and Computer Science), vol. 3, no. 1, pp. 55–60, 2020.
R. Umar, I. Riadi, U. Ahmad Dahlan Yogyakarta, J. D. Soepomo, and K. Umbulharjo, “Klasifikasi Kinerja Programmer pada Aktivitas Media Sosial dengan Metode Support Vector Machines,†CYBERNETICS, vol. 4, no. 01, pp. 32–40, 2020.
M. R. Alghifari and A. P. Wibowo, “Penerapan Metode K-Nearest Neighbor Untuk Klasifikasi Kinerja Satpam Berbasis Web,†2019.
P. R. Sihombing and O. P. Hendarsin, “Perbandingan Metode Artificial Neural Network (ANN) dan Support Vector Machine (SVM) untuk Klasifikasi Kinerja Perusahaan Daerah Air Minum (PDAM) di Indonesiaâ€.
L. Iryani, “PENERAPAN MACHINE LEARNING DALAM KLASIFIKASI KINERJA PEGAWAI PT X,†Jurnal Informanika, vol. 09, no. 01, 2023, [Online]. Available: https://3.bp.blogspot.com/-
I. Hajiali, A. M. Fara Kessi, B. Budiandriani, E. Prihatin, M. M. Sufri, and A. Sudirman, “Determination of Work Motivation, Leadership Style, Employee Competence on Job Satisfaction and Employee Performance,†Golden Ratio of Human Resource Management, vol. 2, no. 1, pp. 57–69, Feb. 2022, doi: 10.52970/grhrm.v2i1.160.
Fauziah, M. A. Tiro, and Ruliana, “Comparison of k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM) Methods for Classification of Poverty Data in Papua,†ARRUS Journal of Mathematics and Applied Science, vol. 2, no. 2, pp. 83–91, Mar. 2022, doi: 10.35877/mathscience741.
I. G. Hendrayana, D. G. H. Divayana, and M. W. A. Kesiman, “KOMPARASI METODE SVM, K-NN DAN NBC PADA ANALISIS SENTIMEN,†Jurnal Indonesia : Manajemen Informatika dan Komunikasi, vol. 4, no. 1, pp. 191–198, Jan. 2023, doi: 10.35870/jimik.v4i1.157.
A. P. Wibawa, M. Guntur, A. Purnama, M. Fathony Akbar, and F. A. Dwiyanto, “Metode-metode Klasifikasi,†Prosiding Seminar Ilmu Komputer dan Teknologi Informasi, vol. 3, no. 1, 2018.
R. Djutalov, “ANALISIS SUKSESI SDM MENGGUNAKAN ALGORITMA KLASIFIKASI K-NEAREST NEIGHBOUR DAN ALGORITMA CLUSTERING K-MEANS ( STUDI KASUS : MABES POLRI),†Jurnal Ilmu Komputer JIK, vol. V, no. 1, pp. 24–29, 2022.
I. Melani, B. Priyatna, F. Nurapriani, and S. S. Hilabi, “Implementasi Metode K-Means Clustering Pada Penilaian Kinerja Karyawan PT Kopetri Citra Abadi,†Jurnal Informatika dan Teknologi Informasi, vol. 8, no. 1, pp. 24–30, 2023, [Online]. Available: http://e-journal.janabadra.ac.id/
B. B. Aji, “Sistem Penilaian Kinerja Berbasis Sasaran Kinerja Pegawai (SKP) di Lingkungan Sekretariat Daerah Kota Banjarbaru,†Journal on Education, vol. 05, no. 01, pp. 1057–1064, 2022.
A. N. Arifah, J. Suprijadi, and I. Ginanjar, “Klasifikasi Rumpun Jabatan ASN Berdasarkan Riwayat Pelatihan Menggunakan Multiclass Support Vector Machine,†Jurnal Statistika Teori dan Aplikasi, vol. 1, no. 1, pp. 191–197, 2022, [Online]. Available: http://prosiding.statistics.unpad.ac.id
D. Lorinda and W. Saputro, “Klasifikasi Sistem Pendukung Keputusan Pemilihan Pegawai Terbaik Menggunakkan Metode Algoritma C4.5 (Studi Kasus: Subdit 1 Dit Tipidum Bareskrim Polri Jakarta,†Jurnal Pendidikan dan Konselimh, vol. 4, no. 5, pp. 1080–1093, 2022.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
