Predicting absenteeism factors in the work place through data mining

Abstract

Absenteeism is an employee’s absence from work. Absences of employees can have a major effect on company strategies, finances, morale and other factors. Excessive absences may influence to decrease productivity of the company. Poorly performing employees cause significant losses to the organization, and absenteeism is considered one of the factors affecting performance. Therefore, understanding the causes of absenteeism can provide organizations with competitive advantage tools and open up research areas for computers and human resources fields. The purpose of this paper is to use computerized technology to discover the causes of employee absence. This study analyzes data from the absentee database and finds several factors that have a good correlation with absentees. In addition, two data mining techniques clustering and association rule mining are used to discover factors which cause in absenteeism with high accuracy. This research paper is to create association model to predict whether find the relationship of absenteeism of employee.