Applying machine learning in data analytics of human resource management

Abstract

Human Resource Management (HRM) plays a crucial role in achieving organizational success by effectively managing the workforce. Every business success has numerous contributions from employees at all levels. However, this becomes an intense dilemma when they leave, which leads to business delays and lower performance. Therefore, employee retention management plays a vital role, which, if well-controlled can enhance the business performance. This research suggests an employee attrition prediction model as well as reports to have an overall view of IBM’s HR dataset. The authors proposed machine learning models to predict employees who left the company: Logistics Regression, K-nearest Neighbors, Decision Tree, Support Vector Machine, Neural Network, and Random Forest. In addition, dashboard reports are also created to support an executive view for business decision-making. By implementing the proposed models and building dashboards, organizations can make use of valuable output to drive suitable strategic HRM decisions and gain meaningful results for business.