C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education - Darmawan, Erlan (Department of Informatics, UIN Sunan Gunung Djati Bandung, 2018)
Data mining has a background with the condition of an abundance of data (the overload data) and the explosion of information faced by companies, institutions, or organizations that have been stored for many years. This situation is also faced in several universities that store various kinds of data, especially new admissions databases. However, the abundant data has not been widely used in digging the information or knowledge that can help university management in making strategic plans. Every year there are new students who retire and do not register, therefore, it takes an application that can process a lot of data to find out the possible retirement for new students. To find out the prediction of retirement prospective students, this paper uses C.45 algorithm. The method can change the very large fact into a decision tree that represents the rule. The result of this research is the application can classify the new students in a tree structure in order that it can produce a rule. This application is able to predict the possibility of the retirement of the new student. With this application, it is expected that the possibility of a prospective student retiring from college can be known at an early stage, so the management can make a decision easily. Development of this application uses PHP as the interface application system and MySql in-database processing. The system development methodology uses the waterfall model