Sistem Rekomendasi Konsentrasi Berdasarkan Aggregate Function Multi Criteria Pada Prodi Informatika UK Petra - Willy Santoso; Rolly Intan; Yulia Yulia (Universitas Kristen Petra, 2022)
The Recommendation system is a system that uses to help users in making decisions by providing item recommendations to the user. In lectures, students are faced with the choice to take a certain concentration of study. However, students are often confused about which concentration of study should they take. Therefore, a system that can provide concentration recommendations is needed so that it can help students in making decisions on choosing the best consentration.Previously there had been a thesis to solve a similar problem using User Based Collaborative Filtering method. In this research the method that will be used is Aggregate Function.Aggregate Function is used to combine the results of the three criteria. The implementation of the Aggregate Function is done by calculating the average value of each concentration from the results of each criterion. The results of the first criteria are obtained using the User Based Collaborative Filtering method based on the Adjusted Cosine Similarity Algorithm. The results of the second criteria are obtained by calculating the average value of the certain mandatory courses that have been taken by the user. The results of the third criterion are obtained by calculating the average value of user preferences in a professional field.Testing of the recommendation system is done by using confusion matrix by measuring the value of accuracy of the recommendation system. The result of this research is the order of concentration recommendations that are suitable for the user based on the use of the Aggregate Function. The results of the tests that used on 30 users obtained 73.3% accuracy rate.