@article {10.3844/jcssp.2020.1001.1010,
article_type = {journal},
title = {Intelligent Attendance System Using Artificial Neural Network Based on Students’ Background},
author = {Abdullah, Daban Abdulsalam and Wakil, Karzan and H.H. Alshatri, Shwan},
volume = {16},
number = {7},
year = {2020},
month = {Jul},
pages = {1001-1010},
doi = {10.3844/jcssp.2020.1001.1010},
url = {https://thescipub.com/abstract/jcssp.2020.1001.1010},
abstract = {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.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}