PENERAPAN ALGORITMA C4.5 UNTUK KLASIFIKASI PREDIKAT KELULUSAN MAHASISWA FAKULTAS KOMUNIKASI DAN INFORMATIKA UNIVERSITAS MUHAMMADIYAH SURAKARTA

Abstract

The growth of database technology in educational system lead to sustainable and abundant students data continue to be generated. Meanwhile, the abundant data can be used for data mining as a source of strategic information in order to achieve better education management. Faculty of Communication and Informatics, Muhammadiyah University of Surakarta (FKI UMS) until the end of 2013 has had as many as 2358 students including those that have passed of approximately 700-800 students. If these data is only accumulated, it will become a burden database. This study was conducted to utilize the abundant data as strategic resources for faculty and department to classify the students’ degree of excellence using data mining techniques.The students’ degree of excellence was classified using the C4.5 algorithm. The number of samples was determined using the equation of Slovin. There are 341 students’ data taken from the total 2358 of FKI students who have graduated as the data to be classified. Data processing was conducted on the separation of the attributes needed for data mining process, standardization of data (preprocessing), and the conversion of real data into nominal data. Attributes used consists of school major (equivalent to high school), gender, home schools, the average number of credits per semester, and assistant roles that are considered important in influencing students’ degree of excellence. The result shows that the highest variable influencing students’ degree of excellence is their participation as an assistant with the accuracy of 73.91%. The result of the study indicates that the variable to use as consideration for faculty to obtain maximum degree of excellence is student participation become an assistant.