Classification Analysis Using C4.5 Algorithm To Predict The Level of Graduation of Nurul Falah Pekanbaru High School Students - Fana Wiza; Bayu Febriadi (Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa, 2019)
School as one of the processes for implementing formal education is required to carry out the learning process optimally to produce quality students. Regarding the research process carried out to predict the graduation rate of SMA Nurul Falah students by using the decision tree method. The data used in this study are student data using the criteria for student names, majors, average report cards from semester one (I), two (II), three (III), four (IV), five (V), and the average value of the National Standard School Examination (USBN). The data is then managed using Rapidminer 5.3 software to make it easier to predict student graduation rates. The application of data mining is used to predict the graduation rate by using the decision tree method and C4.5 algorithm as a supporter as well as to find out information on the graduation rate of Nurul Falah High School students. This study aims to predict student graduation rates in order to get useful information and the school can make policies in the coming year.