Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5

Indah Puji Astuti

Abstract

The student is one of entities in University or Higher Education. The student has a variety of data, such as self-identity information such as address, type of school, work of parents, type of class, etc. In fact many students whose graduation rate is different, on time and not on time. The number of students who graduate is not on time will be a problem not only for university but also for faculty. The number of students graduating each year is one of points of assessment when faculty or study program submits accreditation. C4.5 Algorithm is one of classification algorithm with decision trees. In this study conducted an analysis of student data Engineering Studies Program University of Muhammadiyah Ponorogo 2012/2013. The decision trees in this case is useful for exploring student data, finding the hidden relationship between a number of candidate input attributes with a target attribute. The input attribute consist of, the type of school, address, work of parent, and type of class. The output attribute to classify is status, which consists of "on time" and "not on time". The results from this analysis shown that in this case the C4.5 algorithm can predict with an accuracy value only 82%.

Keywords

Algoritma C4.5; student data; data mining; decision tree

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