Implementasi Algoritma Naïve Bayes untuk Sistem Rekomendasi Pemilihan Fakultas di Universitas Amikom Yogyakarta

Abstract

When someone experiences obstacles in making decisions that must be done, they will usually ask for recommendations from those around them. Similarly, when a prospective student has difficulty determining the faculty when they want to continue their education to the higher education level, they will ask for recommendations from those closest to them who have not provided objective recommendations in accordance with their potential, even though a person's potential is very instrumental in making faculty selection decisions so that they can achieve learning success which can be seen from the achievement index. The same happened to prospective students of Amikom University Yogyakarta. It is necessary to build a system of recommendations for faculty selection. The potential of prospective students explored in this study includes school origin, personality expression, and the values of several subjects that have been obtained in high school. Cluster sampling was chosen to determine respondents where the Faculty as a cluster, respondents were selected from the student population who had taken at least 4 semesters with a grade point average of at least 3.00. The application of the Naïve Bayes algorithm in this study shows good accuracy results so that it can be used on research objects, but it would be more perfect if this system is later developed again into a recommendation for the selection of smaller educational units, namely study programs.