KOMPARASI ANALISIS PENERIMAAN KARYAWAN MENGGUNAKAN ALGORITMA C4.5, K-NN DAN NAÏVE BAYES BERBASIS PSO

Abstract

HRD try do the best for recruitment of employes. However, despite the best possible acceptance process, they found the problem where employee is out before end of contract. To fixed this problem, the authors conducted an existing employee acceptance analysis using the PSO algorithm C4.5, K-NN and Naïve Bayes in order to reduce the existing turnover rate. And the results of this research produce the best accuracy results using the PSO-based Naïve Bayes algorithm with accuracy of 91.25%, precision 88.50,% and recall of 0.94.17% and AUC graph score of 0.903 compared to PSO-based C4.5 algorithm that produces accuracy 86 , 25%, precision 80.83% and recall 68.33% and the AUC 0.530 graph and PSO-based K-NN algorithm which produces accuracy 82.50%, precision 84.33% and 75.00% recall and AUC chart value 0.796