Open AccessImplementasi Data Mining dengan Algoritma C4.5 untuk Memprediksi Tingkat Kelulusan Mahasiswa
Author(s) -
David Hartanto Kamagi,
Seng Hansun
Publication year - 2014
Publication title -
ultimatics : jurnal ilmu teknik informatika/ultimatics : jurnal teknik informatika
Language(s) - English
Resource type - Journals
eISSN - 2581-186X
pISSN - 2085-4552
DOI - 10.31937/ti.v6i1.327
Subject(s) - graduation (instrument) , drop out , computer science , mathematics education , graduate students , medical education , psychology , mathematics , medicine , geometry , economics , demographic economics
Graduation Information is important for Universitas Multimedia Nusantara which engaged in education. The data of graduated students from each academic year is an important part as a source of information to make a decision for BAAK (Bureau of Academic and Student Administration). With this information, a prediction can be made for students who are still active whether they can graduate on time, fast, late or drop out with the implementation of data mining. The purpose of this study is to make a prediction of students’ graduation with C4.5 algorithm as a reference for making policies and actions of academic fields (BAAK) in reducing students who graduated late and did not pass. From the research, the category of IPS semester one to semester six, gender, origin of high school, and number of credits, can predict the graduation of students with conditions quickly pass, pass on time, pass late and drop out, using data mining with C4.5 algorithm. Category of semester six is the highly influential on the predicted outcome of graduation. With the application test result, accuracy of the graduation prediction acquired is 87.5%.
Index Terms-Data mining, C4.5 algorithm, Universitas Multimedia Nusantara, prediction.