PERFORMANCE OF STUDENT PREDICTIONJournal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.8, No. 6)
Publication Date: 2019-06-30
Authors : Mohammed Afzal Ahamed; Prayuk Chaisanit; Mahesh T R;
Page : 45-50
Keywords : Bayes; Naive Bayes; Clustering; Data analysing; Classification algorithm;
Data mining has been successfully implemented in the business and technology world in these days, its use in high education and still relatively new. In the term of education data mining would help the institution to come up with their student performance including academic performance, attendance and if the candidates participated in any activities. Using data mining the aim was to develop a model which can derive the conclusion on students' enrolment behaviour. Different methods and techniques of data mining were compared during prediction of students' enrolment. This paper is supporting the technique that will help the institute to analyst the prediction of admission in which department student's intent to enrol in this institution. It contributes the techniques that would help to predict the performance of students by using the attendant, their work performance, and their behaviours in classes also their performing in the test in each month. The system also proposes an enhanced data mining technique like Bayes algorithm which helps to predict the performance of student by their given data also Cluster technique to separate each student's performance in a different group.
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Last modified: 2019-06-07 20:26:30