Graduation rate is one of the parameters of the effectiveness of educational institutions. The decrease in student graduation rate affects college accreditation. University database stores student administration and academic data, if explored appropriately using data mining techniques, it can be known patterns or knowledge to make decisions. The naive bayes algorithm aims to measure the level of accuracy to be applied in the case of student graduation timeliness. The Naive Bayes method is a classifier with probability and statistical methods to predict future opportunities based on past experience. This research uses student data of Informatics Engineering Education program of Padang State University class of 2011. The variables used in this study were: NIM, name, gender, entry status, GPA, area of origin and employment status. Based on the test results by measuring the performance of the method, it is known that naive bayes has a good accuracy value of 93.48%. From the accuracy value can be concluded that the algorithm naive bayes have a good performance in predicting the timeliness of student graduation.