ANALISIS DATA MINAT CALON MAHASISWA UNIVERSITAS PAMULANG DENGAN MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER - Eko Suharyanto; Afrizal Zein (Institut Sains dan Teknologi Nasional, 2022)
Abstract Pamulang University is a university engaged in education with various majors, ranging from Economics, Law, Engineering, Literature and Education. Unpam has difficulty managing the data of prospective students who enter in determining student interest in choosing existing majors, so which majors are most in demand by prospective students cannot be known by the campus and cause difficulties in determining which majors will be marketed. To support in determining which majors will be marketed and prioritized, the Naïve Bayes Classifier Method is used to help provide solutions in predicting the interest of prospective students in the majors in the data in the previous semester. The research data in the form of secondary data obtained from the IT-Center of Pamulang University is 5142. The data will then be analyzed to map the patterns of interest of prospective students at Pamulang University using the Naïve Bayes Classifier Method. The results of the analysis of the Naïve Bayes Classifier Method show that the interest of prospective students who will enter UNPAM is dominated by the Faculty of Economics majoring in Management 45.19%, Informatics Engineering 22.09%, Accounting 13.71%, Civil Law 13.57% and Information Systems 5 ,48% Thus, it can assist in determining what majors are most in demand by prospective students according to their needs and desires and produce alternative choices of other majors. Keywords: Data Analysis, Naive Bayes, and Classifier