Study Program Classification System Informatics Engineering of Ubhara Surabaya - Wahyu Dyah Rizki Septiana; Eko Prasetyo; Rani Purbaningtyas (JEECS (Journal of Electrical Engineering and Computer Sciences), 2020)
One indicator to improve the quality of a university is the number of students who graduate on time. But the problem that often occurs at Bhayangkara University in Surabaya is the number of students entering and the number of students graduating unbalanced. Therefore this research was made to classify the period of study of students by using variables in the form of social studies semester 1-4, school origin, work status, morning / evening class status, and sex. This study aims to classify the length of time a student studies on time or late using the naïve bayes method. The results of this study indicate that the system is able to classify training data and test data on experiments conducted in each batch, the highest accuracy results are 59% and the lowest accuracy results are 56%.