Evaluasi Algoritma Klasifikasi Machine Learning Kategori Nilai Akhir Tunjangan Kinerja Pegawai

Abstract

Allowance is a gift of appreciation for services in the form of an imbalance in work performance or performance dipsplayes. AT the moment the agency has not used the final value category for employee salary allowances, the program needed to determine the final category of employee benefits with a Machine Learning approach using the C4.5 and Naive Bayes Gaussian algorithms and evaluation of prediction results using Confusion Matrix and K-FOLD Cross Validation. The purpose of this research is to results of classification predictions in the category of using the final salary of employees of Confusion Matrix and K-FOLD Cross Validation. After mining the data, the performance of each algorithm is evaluated determine mining success rate process on the C4.5 and Naive Bayes Gaussian algorithms. Then the result is obtained and the C4.5 algorithms is a better algorithm in determining the category of employee salary allowance values.