Sistem Pendukung Keputusan Rekomendasi Topik Skripsi Menggunakan Naïve Bayes Classifier

Abstract

Every student is required to carry out an obligation, one of which is in the form of research. As a tangible form of the final process towards undergraduate each student is required to make scientific articles in the form of books which are named thesis. So far, the process of determining student thesis topics is done manually, both thesis supervisors who provide input or ideas are obtained from various research papers. And the process of determining the thesis topic without using a computerized system. Therefore, researchers made this research in order to assist students in determining the thesis topic according to student competencies. This research method uses data mining and software development methods by applying the Naïve Bayes Classifier algorithm to a website-based system. The result of this research is a decision support system that can provide thesis topic recommendations based on the value data of the elective courses. The best accuracy model value implemented in this system is 69.27%. The accuracy value is not good because the amount of data is not balanced in each category of the thesis topic.