Research Article

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

by  Priyanka Saini, Ajit Kumar Jain
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 84 - Issue 14
Published: December 2013
Authors: Priyanka Saini, Ajit Kumar Jain
10.5120/14646-2966
PDF

Priyanka Saini, Ajit Kumar Jain . Prediction using Classification Technique for the Students’ Enrollment Process in Higher Educational Institutions. International Journal of Computer Applications. 84, 14 (December 2013), 37-41. DOI=10.5120/14646-2966

                        @article{ 10.5120/14646-2966,
                        author  = { Priyanka Saini,Ajit Kumar Jain },
                        title   = { Prediction using Classification Technique for the Students’ Enrollment Process in Higher Educational Institutions },
                        journal = { International Journal of Computer Applications },
                        year    = { 2013 },
                        volume  = { 84 },
                        number  = { 14 },
                        pages   = { 37-41 },
                        doi     = { 10.5120/14646-2966 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2013
                        %A Priyanka Saini
                        %A Ajit Kumar Jain
                        %T Prediction using Classification Technique for the Students’ Enrollment Process in Higher Educational Institutions%T 
                        %J International Journal of Computer Applications
                        %V 84
                        %N 14
                        %P 37-41
                        %R 10.5120/14646-2966
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Educational Data Mining Decision Tree Algorithm (ID3 J48) WEKA.

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