Prediction of New Student Registration at Universitas Muhammadiyah Yogyakarta using the Naïve Bayes Classification Algorithm

All public and private universities perform new student admission each year, with the number of applicants reaching thousands. Prospective students who intend to continue meet higher education criteria must re-register according university’s timetable after enrolling through their selected pathway being pronounced passed. Due movement prospective different departments or universities, applications typically does not match individuals have re-registered. If probability a candidate departing can be discovered early, management take necessary steps retain student. Data mining Naïve Bayes algorithm were employed analyze data. The information was extracted from Universitas Muhammadiyah Yogyakarta’s database Information Technology freshmen for 2016-2017. Microsoft Excel, RapidMiner, SQL Server 2014 Management Studio utilized.