Advisor-Oriented Course Recommendation System Using Student Grades - Pangestu, Muftah Afrizal; Karnalim, Oscar (Universitas Andalas, 2023)
In some universities, student advisors are often hired to enhance students’ retention rate. Having some students in mind, these advisors may ﬁnd some difﬁculties in guiding the students in terms of selecting relevant courses. This paper proposes an advisor-oriented course recommendation system. Using this system, the advisors may suggest relevant courses to their students easier and more accurate. This system relies on student grades and comprehensive course data. Further, it utilises content-based and collaborative ﬁltering for predicting relevant courses. According to our evaluation, the system is considerably effective; the accuracy of content-based ﬁltering is about 66% while the accuracy of collaborative ﬁltering is about 58%. Further, some parameters may be potential for enhancing accuracy while the others may be not.