Sistem Prediksi Penerimaan SNMPTN menggunakan Algoritme Decision Tree C4.5 - Dityo Kukuh Utomo; Ahmad Afif Supianto; Welly Purnomo (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Seleksi Nasional Masuk Perguruan Tinggi Negeri (SNMPTN) is a selection of tertiary education based on the grade of subjects which each year experiences an increase in the number of participants so that they have a high level of competition. Counseling guidance teacher has the duty to predict student acceptance in attending SNMPTN. Problems arise when the number of students conducting guidance increases as the SNMPTN registration time approaches. Therefore, we need a system that can predict the likelihood of students being accepted through the SNMPTN pathway to ease the burden on counseling guidance teachers. One prediction algorithm is decision tree C4.5 that makes decision tress to describe rules. The data used comes from the value of subjects belonging to SMA Negeri 3 Malang alumni who have attended SNMPTN from 2016-2018 with a total of 681 data for the Natural Sciences majors and 90 data for the Social Sciences majors along with a list of students graduating SNMPTN in the same year. From the value data and the list of students passing the SNMPTN, the attribute used is only the attribute value of the subjects used in the 2019 SNMPTN along with the status of graduating or not students in joining the SNMPTN. The system is built in the form of a website that utilizes WEKA CLI for the prediction process. The black box testing-validation results show the use case and system functions are matched or valid. The system usability level generated by utilizing the system usability scale is 87.5 which is included in the