In the current world, the behavior of students changes from time to time, based on their emotional decisions regarding the kind of activities they are involved with. Many emotions are produced by the students when they act in a particular incident-based activity. This research work, analysis such kind of emotion-based students’ personalities through their activities using some of the data mining techniques, Naive Bayes and Random Forest are utilized to predict the usefulness of the students’ activities, created utilizing their decisions. The data set is collected from the students for this analysis employing a questionnaire. The performance of both algorithms is evaluated based on the results of students' decision-making responses collected from the survey. The best algorithm for the analysis of emotional intelligence-based students’ information is suggested based on the accuracy of the algorithms.

Data Mining Algorithms, Emotional Intelligence, Naïve Bayes Algorithm, Random Forest Algorithm, Performance Accuracy.