Analyzing Primary Student Data Using Data Mining

• Main Author: Chong, Sze Wei
• Format: Thesis
• Language: English; English
• Published: 2009
• Subjects: QA76 Computer software
• Online Access: http://etd.uum.edu.my/1574/1/Chong_Sze_Wei_801162_%282009%29.pdf; http://etd.uum.edu.my/1574/2/1.Chong_Sze_Wei_801162_%282009%29.pdf; http://etd.uum.edu.my/1574/

Nowadays, academic achievement has become the most important evidence for establishing the value of Malaysia’s education boundary. In this study, the primary students’ examination data is collected on the previous examination mark yet sake to be analyzed for their future study plan. The selection of using data mining approaches was based on the capability of data mining as a grateful tool for academic analysis purposes. Focused on educational boundary, data mining approaches can be used for the process of uncovering hidden information and patterns that can help school community forecast the students’ academic achievement. Therefore, the other relevant data such as student performance information and family income also engaged in this study. The overall relevant raw datasets is used for preprocessed and analyzed using statistical method. In addition, the result from the statistical manner analysis point out the considerable contribution of these attributes to the academic achievement plan.