Employee attitudes stand out among the most repetitive causes of absenteeism, while employee turnover, organizational health, and employee absenteeism loss provide a flexible framework for predicting employee absenteeism to support HR decisions. • We predict employees at risk of absence without having health variables. •, This systematic review and analysis shows that different machine learning methods have been used to predict absenteeism and temporary disability. Multiple, Abstract. This study aimed to investigate the reasons for truancy among students in different types of secondary schools and among school counselors. This study provides insight into the effects of truancy on academic and social-emotional development across a wide range of grade levels and for several subgroups of students. As such, absenteeism constitutes an essential problem for companies throughout their economic life cycle. Unexpected absenteeism results in additional workload for other staff members and, firstly, examining the effects of different risk factors for absenteeism and school dropout increases fundamental knowledge about the etiology of these behaviors. The proportion of students attending schools with "high" or "extreme" rates of chronic absenteeism increased percent over - year percent over - 6. Follow and enforce written policies. Employee attendance and lateness policies should be clearly written and consistently followed and enforced. Attendance will generally increase when employees. 6. Conclusions and implications. This study found that self-inflicted stress, time management stress, group work stress, and performance stress were predictors of mental health, supporting the hypothesis that there is a negative relationship between academic stress and mental health of university students. the paper is. to use the multinomial logistic regression model for employee absence classes. TRUE. Positive, true negative, false positive, false negative, precision.