Employee performance prediction using different supervised classifiers

Abstract

Employee performance evaluation intends to measure the commitment of everyone in the company. Predicting employee performance is essential for company’s success. This paper presented employee performance prediction in a company using machine learning. The researcher follows Cross-industry standard process for data mining (CRIPS-DM). Logistic Regression, Decision Tree, and Naïve Bayes classification method are used to develop the prediction model. The result shows that Logistic Regression has higher accuracy with the other two classifier used.