Graduation Prediction Application using Naive Bayes Algorithm in Sukabumi Muhammadiyah University - Indra Griha Tofik Isa; Indra Satriadi (Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa, 2022)
The use of data mining has become a trend in data processing because of the availability of large amounts of data and the increasing need to convert this data into useful information and knowledge. Besides as a tool in extracting data, data mining is also used as decision support, both in the commercial and non-commercial fields. Of the many algorithms used in data mining, one of them is the Naïve Bayes Algorithm, which in this algorithm is one of the methods in Probabilistic Reasoning which aims to classify data in certain classes. The study conducted by applying the stages of the Naïve Bayes Algorithm in application design to predict student graduation on time based on the parameters contained in the Enrolment Student (PMB), Grade Point Average (IP) and the Finance Department. The data processed were 436 datasets from the Informatics Engineering Study Program, Muhammadiyah University of Sukabumi. The system design uses UML modeling with implementation using the PHP programming language and MySQL database. The results of the study are in the form of graduation prediction applications with an accuracy rate of 78%