EFFECTIVE INTELLECTUAL METHODS USED IN PERSONNEL SELECTION

Abstract

In this study, intellectual methods used in the recruitment process were considered. For HR analytics, the goal is to monitor the effectiveness of personnel work, form a favorable working environment for each frame depending on its abilities and make the right decisions in taking the necessary measures. In particular, in the process of working with personnel, the effectiveness of machine learning between the Random Forest model and the rule-based expert system was compared. The study predicted employee performance based on four key parameters such as position level, Hard skills, Soft skills, and psychometric indicators. Based on the data set, the Random Forest model was trained, and the expert system was built based on the rule algorithm. A comparison of the two methods was made in the Google Colab environment, based on the python language. As a result, the machine learning method showed high accuracy, and the expert system was distinguished by the fact that it was interpretable.