DESIGN AND IMPLEMENTATION OF STUDENTS PERFORMANCE ANALYSIS SYSTEM (A CASE STUDY OF DELTA STATE POLYTEHNIC OZORO)

The ability to predict the performance tendency of students is very important to improve their teaching skills. It has become a valuable knowledge that can be used for different purpose; for example, a strategic plan can be applied for the development of a quality education. This paper propose the application of data mining technical and graph to predict the performance of student based on their historical data. In the experimental studies, three well-unknown data mining techniques (decision tree, random forest, and naive Bayes) were employed on the institution datasets related to all course offered by student in a particular department. The results showed the effectiveness of data mining learning techniques when predicting the performance of student and how graph can used to make the analysis of the data easily readable and understandable. VB.Net programming language for frontend design, Microsoft access database for backend design. While Rapid Application Development (RAD) was adopted as the system’s research methodology during the development stage.