ANALISA KLASIFIKASI KUALITAS MAHASISWA LULUSAN BERDASARKAN JALUR PENERIMAAN MENGGUNAKAN ALGORITMA C4.5 (STUDI KASUS: UNIVERSITAS LAMPUNG)

Abstract

Universities need a quality evaluation process based on the standards of the National Accreditation Agency for Higher Education (BAN-PT) every year. Therefore, it is necessary for universities knowing the students to evaluate and to maintain the University's Education Efficiency Number (AEE). One of the standards that has been determined by BAN-PT is the quality of students that can be seen from the GPA, the accuracy of completing studies, thesis, path admission, and others. The purpose of this study is to provide information about the quality of students based on SNMPTN and SBMPTN admission with data mining techniques using RapidMiner software in the application of the C4.5 algorithm and using the research method of the Cross-Industry Standard Process for Data Mining (CRIPS-DM). The results of this study were students who has graduated of class I quality was 46% from the SBMPTN path admission, 28% of the SNMPTN path admission, and class II category was 11% from the SBMPTN path admission, and 15% from the SNMPTN path admission. The results of accuracy obtained in decision tree modeling got an accuracy value of 97.46% with an error value of 0.98% and the value of Area Under Curve (AUC) of 0.973 with an error value of 0.014 which is classified into a excellent classification.