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Intan Murni Pratiwi
Universitas Buana Perjuangan Karawang
Computer Science & IT

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PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PREDIKSI PENERIMAAN KARYAWAN Intan Murni Pratiwi; Ahmad Fauzi; Santi Arum Puspita Lestari; Yana Cahyana
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1282

Abstract

The number of job seekers keeps growing, as does the quantity of companies that open job vacancies and offer opportunities to prospective employees. In terms of recruiting new employees, companies are very selective.. Companies are very selective in accepting prospective workers, where prospective workers must have qualifications that are in accordance with the positions needed in the company, because employees are an important asset in the growth and development of the company. because employees are an important factor in the growth and development of the company. Quality companies need good employees. This research uses employee recruitment data from PT Atma Darma Apta. The data has 372 rows and 8 attributes. The Naïve Bayes algorithm and the assessment techniques Mean Squared Error, Root Mean Squared Error, and R2 Score are used in this study. The results showed that the algorithm obtained good results by using a 90 to 10 data division resulting in a large accuracy value of 97.14%. In addition, the MSE, RMSE, and R2 Score values have quite good results, which are 2.86, 16.90, and 1.00. The 70 to 30 data division produces poor values with error values of 152.80 and 123.60, but the accuracy and R2 Score values are quite large at 96.15% and 0.95. With these results, this research can be continued into an application that can predict employee selection results.
Co-Authors Ahmad Fauzi Lestari, Santi Arum Puspita