International Journal of Academic Engineering Research (IJAER)   Year: 2020 | Volume: 4 | Issue: 9 | Page No.: 62-67 Artificial Neural Network for Predicting Workplace Absenteeism Raghad Adnan Abu Hassanein, Saja Ahmed Al-Qassas, Fatima Naji Abu Tir, Samy S. Abu-Naser Abstract: Associations can grow, succeed, and sustain if their employees are committed. The main assets of an association are those employees who are giving it a required number of hours per month, in other words, those employees who are punctual towards their attendance. Absenteeism from work is a multibillion-dollar problem, and it costs money and decreases revenue. At the time of hiring an employee, Associations do not have an objective mechanism to predict whether an employee will be punctual towards attendance or will be habitually absent. For some Associations, it can be very difficult to deal with those employees who are not punctual, as firing may be either not possible or it may have a huge cost to the association. In this paper, we propose An Artificial Neural Networks algorithm that can predict the behavior of employees towards punctuality at workplace. The efficacy of the proposed method is tested with traditional machine learning techniques, and the results indicate 99.00% accuracy. The proposed model will provide a useful mechanism to associations that are interested to know the behavior of employees at the time of hiring and can reduce the cost of paying to inefficient or habitually absent employees.