A Student Advising System Using Association Rule Mining

Academic advising is a time-consuming activity that takes considerable effort in guiding students to improve student performance. Traditional systems depend greatly on the of advisor find best selection courses performance next semester. There need know associations and patterns among course registration. Finding can guide direct selecting appropriate leads improvement. In this paper, authors propose use association rule mining help both advisors prioritizing courses. Association rules dependences based their previous The conducted thousands records between have been registered by many semesters. system has successfully generated list particular select was validated registration 100 students, precision recall showed acceptable prediction