Prediction using Classification Technique for the Students' Enrollment Process in Higher Educational Institutions

In recent years, Indian higher educational institutes grow rapidly. There is more competition between institutes for attracting students to get enrollment in their institutes. The admission process is conducted every year at the institute and it results in the recording of large amounts of data. But, in most of the cases this data is not properly utilized (or analyzed) and results in wastage of what would otherwise be one of the most precious assets of the institutes. By applying the various data mining techniques on this data one can get valuable information and predictions can be done for the betterment of the admission process. This study presents data mining techniques for the enrollment process in MCA stream. These methods will help to improve the overall performance of the admission process at higher educational institutes. General Terms Data Mining, Classification, Data Preprocessing, KDD