An Approach to Predict Student Results using J48 Algorithm and Data Mining Tool

Abstract: One of the most global challenges met by the data analyst is to analyze large amount of stored data and extract essential information. The task of extracting the data is required for future predictions in many sectors of that matter. The predictions are made using forecasting models to take necessary actions for decision policy making. J48 Decision tree algorithm is one of the best techniques to make predictions on nominal data. The paper focuses on implementing and proposes an approach to predict Student results using J48 Algorithm. The entropy of information is measured using student dataset. Based on the predictions made, the educational institutions can make decisions to improve the quality of results. The task is carried out using Data mining tool such as Weka.

Keywords: J48 Algorithm, Decision Tree, Forecasting models, Nominal data, Data mining tool, Weka.