KLASIFIKASI KELAYAKAN PEGAWAI KONTRAK MENJADI PEGAWAI TETAP MENGGUNAKAN METODE NAIVE BAYES

Authors

  • Muh. Rosyid Khoirudin
  • Muhammad Hasbi
  • Bebas Widada
  • Khoirul Akhyar
  • Kumaratih Sandradewi

DOI:

https://doi.org/10.30646/tikomsin.v12i2.863

Keywords:

Naïve bayes, Classification, Data Mining

Abstract

Employees are the most important asset in the ongoing activities and programs that have been designed by the foundation and the emergence of difficulties in determining the status of new staff at the foundation, because the manual system is still in effect, from written exams, oral exams and interviews. which allows the loss of files in testing and lack of objectivity in giving an assessment to employees. Therefore, this research was conducted to help determine the eligibility of foundation employees to be classified into "Eligible" and "Not Eligible" to be appointed as permanent employees of the foundation. The method implemented in this study uses the Naive Bayes classifier method in determining classification, in research testing using the Confussion Matrix validity testing method. The creation of a foundation employee classification system using the Naive Bayes method, which can determine the classification results based on the results of Eligible and not eligible to be appointed as permanent employees of the foundation. the test results obtained from the study used 50 data, with details of 35 as training data 15 training data obtained an accuracy of 86.7%. from here which shows that this program can be used as a reference in determining the eligibility status of permanent employees at the Smart Cendekia foundation.

References

E. Poerwandono and J. Perwitosari, “Penerapan Data Mining Untuk Penilaian Kinerja Karyawan Di PT. Riksa Dinar DJaya Menggunakan Metode Naïve Bayes Classification,†J. Sains dan Teknol., vol. 5, no. 1, p. |pp, 2023, [Online]. Available: https://doi.org/10.55338/saintek.v5i1.1416.

D. Remawati, P. Harsadi, and R. D. Nugroho, “Penerapan Sistem Penunjang Keputusan Menggunakan Algoritma Naive Bayes Pada konsep Human Resource Information System (HRIS) (Studi kasus :Penerusan Kontrak Kerja Karyawan di PT. XYZ),†J. Ilm. SINUS, vol. 18, no. 1, p. 63, 2020, doi: 10.30646/sinus.v18i1.440.

A. Sudrajat, “Penerapan Metode Naïve Bayes Untuk Menentukan Penilaian Kinerja Karyawan PT.Sinergi Guna Solusindo,†OKTAL J. Ilmu Komput. dan Sci., vol. Volume 99, no. 99, pp. 1596–1606, 2022, [Online]. Available: https://journal.mediapublikasi.id/index.php/oktal.

F. Ramadhan and H. D. Bhakti, “Klasifikasi Penilaian Kinerja Karyawan Menggunakan Algoritma Naive Bayes(Studi Kasus PT. AS SABAR SUKSES BERKAH),†vol. 4, no. 2, 2024, doi: 10.8734/Kohesi.v1i2.365.

A. J. Susilo, K. K. Kustanto, and D. Remawati, “Implementasi Naïve Bayes Dalam Pemilihan Jenis Bahan Pembuatan Meja,†J. Ilm. SINUS, vol. 21, no. 1, p. 39, 2023, doi: 10.30646/sinus.v21i1.674.

N. Nurainun, E. Haerani, F. Syafria, and L. Oktavia, “Penerapan Algoritma Naïve Bayes Classifier Dalam Klasifikasi Status Gizi Balita dengan Pengujian K-Fold Cross Validation,†J. Comput. Syst. Informatics, vol. 4, no. 3, pp. 578–586, 2023, doi: 10.47065/josyc.v4i3.3414.

D. Remawati and K. Sandradewi, “Journal of Information Technology , Computer Engineering and Artificial Intelligence ( ITCEA ) Metode Naïve Bayes Untuk Prediksi Waktu Produksi Mebel di UD . Wali Barokah Kartasura Sukoharjo Jawa Tengah,†pp. 58–67, 2024.

W. Yulianti1, W. Wiyanto, and N. Nurhidayanti, “Algoritma Naive Bayes Untuk Klasifikasi Perpanjangan Kontrak Kerja Karyawan Pada PT Torini Jaya Abadi,†vol. 5, no. 3, pp. 516–524, 2023.

A. Dwi Septiana, D. Remawati, P. Studi Teknologi Informasi, and S. Sinar Nusantarara surakarta, “Diagnosa Penyakit Antraks Dengan Metode Naive Bayes (Studi Kasus: Kambing Jawarandu),†J. TIKomSiN, vol. 11, no. 2, pp. 53–58, 2023, [Online]. Available: https://doi.org/10.30646/tikomsin.v11i2.787.

H. D. Wijaya and S. Dwiasnati, “Implementasi Data Mining dengan Algoritma Naïve Bayes pada Penjualan Obat,†J. Inform., vol. 7, no. 1, pp. 1–7, 2020, doi: 10.31311/ji.v7i1.6203.

I. A. Prabowo, D. Remawati, and A. P. W. Wardana, “Klasifikasi Tingkat Gangguan Tidur Menggunakan Algoritma Naïve Bayes,†J. Teknol. Inf. dan Komun., vol. 8, no. 2, 2020, doi: 10.30646/tikomsin.v8i2.519.

P. Harsadi, D. Remawati, and K. B. Satrio, “Pemetaan Usaha Cafe Di Manahan Dengan Menggunakan Metode Naive Bayes Studi Kasus Dinas Perdagangan,†J. Teknol. Inf. dan Komun., vol. 8, no. 2, pp. 57–62, 2020, doi: 10.30646/tikomsin.v8i2.522.

D. Alita, I. Sari, A. R. Isnain, and S. Styawati, “Penerapan Naïve Bayes Classifier Untuk Pendukung Keputusan Penerima Beasiswa,†J. Data Min. dan Sist. Inf., vol. 2, no. 1, p. 17, 2021, doi: 10.33365/jdmsi.v2i1.1028.

Heliyanti Susana, “Penerapan Model Klasifikasi Metode Naive Bayes Terhadap Penggunaan Akses Internet,†J. Ris. Sist. Inf. dan Teknol. Inf., vol. 4, no. 1, pp. 1–8, 2022, doi: 10.52005/jursistekni.v4i1.96.

A. Pebdika, R. Herdiana, and D. Solihudin, “Klasifikasi Menggunakan Metode Naive Bayes Untuk Menentukan Calon Penerima Pip,†JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 1, pp. 452–458, 2023, doi: 10.36040/jati.v7i1.6303.

D. A. Punkastyo, F. Septian, and A. Syaripudin, “Implementasi Data Mining Menggunakan Algoritma Naïve Bayes Untuk Prediksi Kelulusan Siswa,†J. Syst. Comput. Eng., vol. 5, no. 1, pp. 24–35, 2024, doi: 10.61628/jsce.v5i1.1073.

Cover

Downloads

Published

2024-10-22

Issue

Vol. 12 No. 2 (2024): Jurnal TIKomSiN Vol 12, No. 2 Oktober 2024

Section

Articles

Citation Check

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 a Creative Commons Attribution License that allows others to share the work with an acknowledgement 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 acknowledgement 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 (See The Effect of Open Access).

 

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.