A STUDY AND ANALYSIS OF EDUCATION DATA USING DECISION TREE ALGORITHMS

Abstract

In today scenario education data mining is a best tool for improving education method and managing academic institutions. Many researchers studied about education data mining in technology and predict new methods, it is useful for academic institutions and higher education if it will implement in education system people get a quality education. Statistical analysis: A classification technique used to the huge amount of data analysis, and predicts future decision and applying in many fields. This proposed study has three stage process, the first stage is input the data to pre processing, second stage applying classification algorithms, namely J48, random forest (RF) tree and reduced-error pruning (REP) tree and final stage is to identify performance. Findings: To find out the classification algorithm's performance, this method used education data as input. Particularly, this work carries out to compare the three algorithms in decision tree algorithms to predict the performance accuracy in the usage of education data.