Class attendance is required of all undergraduates unless the student has an official excused absence. For unexcused absence, the student may be denied the opportunity to make up some or all of the work missed. The student is responsible for class-related work missed as a result of an absence. However, a time of loss is very difficult for a student to be overtaken. The aim of this research is to analyze the causes of students’ unexcused absences. To this end, the behavior of students in terms of attendance needs to be analyzed. Educational Data Mining is common research area that is based on applying Data Mining approaches to better analyze and understand students’ behavior. This research involves the analysis of the attendance behavior of students from historical data using Data Mining techniques to improve students’ performance. The results showed that the university timetabling is the main factor that affects the student’s absences.