Intelligent Attendance System Using Artificial Neural Network Based on Students’ Background
- 1 Sulaimani Polytechnic University, Sulaimani 46001, Kurdistan Region, Iraq
- 2 University of Halabja, Halabja 46018, Kurdistan Region, Iraq
Published On: 21 July 2020
Copyright: © 2020 Daban Abdulsalam Abdullah, Karzan Wakil and Shwan H.H. Alshatri. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Determining the rate of student attendance is an important task in determining the completion of the courses. Despite the success of the technology, it is unfortunate that in many academic institutions, the current systems used to detect student absences. Furthermore, one of the crucial problems in the attendance system does not count student background for continuing in the courses. In this study, we propose an intelligent approach for calculating student attendance based on their Grade Point Average (GPA) and their activities, this approach uses Artificial Neural Network (ANN) for proposing an intelligent attendance system to calculate the attendance rating accurately, meaning the system provide a new rating for each student based on their background. The aim of this research is developing an attendance system for motivation students taking attendance or taking high grade in the class. The result of this approach helps the instructor to allow students who have more activities with more absents to continue in the courses, if not the students have low activity should taking high attendance. This system will more efficient for monitoring students in the classes and replacing absent to activity.
- Attendance System
- Student GPA
- Intelligent Education System