CD Skripsi
Implementasi Algoritma Data Mining C4.5 Untuk Memprediksi Kelulusan Mahasiswa (Studi Kasus Prodi Sistem Informasi Jurusan Ilmu Komputer Universitas Riau)
ABSTRACT
Admission of students every year cause the accumulation of student data, such as personal data, value data, and other’s data. The stack data in the campus’s database is still underutilized. Stacks of student data can be managed and analyzed by using certain fields of science to see the phenomena and characteristics of a data. One of them is by using data mining. The purpose of this study is to implement the C4.5 algorithm model to predict student graduation. Student’s data such as NIM, Entry Path, Regional Origin, Gender, Grade Point Average (GPA), Grade Point Average from the first semester to the fifth semester and student graduation (is it on time or not) will be managed and analyzed using the C4.5 algorithm method. . The results of data management are in the form of decision trees and rules that will be used as criteria for predicting student graduation. Student data was collected using the documentation method by taking existing data through the academic department of the Faculty of Mathematics and Natural Sciences, Riau University and then analyzed using the C4.5 algorithm method. The contribution of the results of this study is a system that can predict student graduation using the same data attributes in the training data, such as NIM, Entry Path, Regional Origin, Gender, GPA, first semester IP to fifth semester IP. In the graduation prediction system designed, from a total of 382 student data processed, the system was found to run well with a prediction accuracy rate of 80.58%. The level of accuracy of the system's prediction accuracy will increase along with the increase in the amount of test/training data in the system. The more data used, the better the system in predicting student graduation rates.
Keyword : Student Graduation, Algorithm C4.5, Data Mining, Riau University.
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