Penerapan Algoritma Naive Bayes Untuk Prediksi Penerimaan Karyawan

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 froNm 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 best model accuracy results using the Naïve Bayes algorithm as well as MSE and RMSE error values with 90 to 10 data division are for accuracy of 97.14%, MSE of 2.86, RMSE of 16.90, and R2 value of 1.00. With these results, in the future this research can be continued by implementing the Naïve Bayes algorithm into applications that can predict employee recruitment.
Keywords: Prediction, Employe, Naïve Bayes, Mean Squared Error, Root Mean Squared Error, R2 Score