Design and application data mining in academic fields

Abstract

Classification is a data mining technique for a process of finding a model that explains or distinguishes a concept or class of data. The goal is to be able to estimate the class of an object whose class is unknown. Seeing the importance of education quality that must increase continuously, the study was conducted to evaluate the educational process in the department based on academic historical academic data which is used as input for which new and unknown classes of objects will be obtained. The level of competitiveness in entering a department in higher education is one of the things that becomes an assessment of department accreditation. Thus it is necessary to analyze how many students accepted into a department do not move to other department the following year. The analysis used C4.5 methods and in the process used Rapid miner software to make decision trees. The results obtained an accuracy rate of around 61.2% with confussion matrix.