C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education - Erlan Darmawan (JOIN (Jurnal Online Informatika), 2018)
Data mining has background with the condition of an abundance of data (the overload data) and the explosion information faced by companies, institutions or organizations that are stored for many years. This situation is also faced in several universities that stores various kinds of data, especially new admissions database. But 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 that 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 retirement prospective students, this paper uses C.45 algorithm. The method can change the a very large fact into a decision tree that represents the rule. The result of this research is that the application can classify the new students in tree structure in order that it can produce a rule. This application is able to predict the possibility of the retirement of new student. With this application, itÂ  is expected that the possibility of a prospective student will retire from college can be known at an early stage, so the management can make a decision easily. Development of this application built uses PHP as the interface application system and MySql in database processing. System development methodology used is the waterfall model