PREDICTIVE ANALYTICS IN HUMAN RESOURCES USING MACHINE LEARNING AND DATA MINING

Abstract

The use of information systems in the field of human resources management (HRM) is gaining popularity as a result of global technological development. The major transformation that worksites have gone through call for the use of Human Resources Information Systems (HRIS) in human resources (HR) practices. The human resources knowledge management field includes rules, patterns, and relationships between data mining and machine learning data analytics and knowledge discovery. Data mining and machine learning are very important and both are used by businesses to turn datasets into useful information. It helps businesses analyze and understand trends that can lead to better business decisions. In the use of data mining, one can choose the right algorithms, set parameters, and prepare models for a particular problem. It requires an expert who can train, and these are expert machine learning tools. Within scope of this study, research was carried out with white collar employees in a company engaged in automotive business in Bursa. The cost, saving of time and strategic effect of the human resources information system on the company and the information technology infrastructure; along with the relationships according to the department, age, gender and educational status were investigated by statistical and data mining. The Knime program was used as a machine learning program. The results of the human resources information system were evaluated and suggestions were made for future planning.