Mining Educational Data to Predict Students' Future Performance using Naïve Bayesian Algorithm

Higher education institutions want not only to provide quality education to its students but also to advice career options according to the prediction of students' performance. The students' satisfactory performance takes an important role to give birth the best quality graduates who will become competent laborers for the country's economic and social development 2 . Students' performance like who will pass and who are likely to fail can be predicted with the help of lots of features available. The students want to realize their final performance before the announcement of their results and before they attend their semester exams. According to their predicted performance, the students can improve their skills by proper planning to lead to a good performance in their end examination. To provide a good advice to such kind of student, educational data mining system is implemented to predict students' final performance evaluated by considering factors which include IM, PSM, Basics, ACIC, ASS, CP, ATT, ACOC and ESM. In this research, an attempt has been made to explore Naïve Bayesian classification to predict the students' future performance. Nilaraye "Mining Educational Data to Predict Students' Future Performance using Naïve Bayesian Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26642.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/26642/mining-educational-data-to-predict-students%E2%80%99-future-performance-using-na%C3%AFve-bayesian-algorithm/nilaraye