Student Academic Performance Prediction System by Using Decision Tree

The main goal of the education system is not only to provide good quality education but to ensure that students can graduate with excellent academic performance. The main challenge of educational institutions is the drop-in rates for the success of students in academics, some even decide to quit studying. To overcome such problems, early forecasting, and analysis related to student failure or factors that may affect academic performance students need to be done. This method can help educational institutions identify students who need special attention to reduce the failure rate and take appropriate action. Storage of information related to student exam results is often collected and kept by the management department of the faculty as a record only. Thus, Student Performance Prediction System is developed using tree classification techniques ID3 results where IF-THEN rules are generated through ORANGE software and applied into the system to be developed. Student information such as results examination, gender, student status, state of origin is collected to help generate tips. Data storage such as user information and information students are stored through a MySQL database. In addition, HTML, CSS, and PHP as well used to design the system interface. Overall, the development of this Student Academic Performance Prediction System by Using Decision Tree is intended to help educational institutions increase the rate of excellence and reduce student dropout or failure rate.