• Mrs. Khushbu Gupta
• Ms. Sonam Katare

Colleges, Institutes and universities have huge amount of students’ data and this data is growing rapidly. Educational Data Mining helps enormously to extract hidden knowledge from this students’ data. In the past, researchers predicted the students’ performance based on their academics’ attributes only, but we realized that there are many other attributes which also affects the students’ academic performance. We have collected data of students’ currently studying in final year as testing data and recently graduated students as training data from Jabalpur city through online survey. This survey consists of 34 questions for final year students and 33 questions for graduated students. Collected data was applied on various classification algorithms such as J48, Naïve Bayes, Random Forest, Random Tree and REPTree using WEKA. The intent of this paper is to find the classifier(s) which gives high accuracy.

Naive Bayes, Decision Tree, J48, REPtree, ID3, Random Forest, Random Tree.

"Prediction of academic performance of undergraduate students in jabalpur", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.451-454, April-2019, Available :http://www.jetir.org/papers/JETIR1904267.pdf

"Prediction of academic performance of undergraduate students in jabalpur", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp451-454, April-2019, Available at : http://www.jetir.org/papers/JETIR1904267.pdf