INTELLIGENT EDUCATION MONITORING SYSTEM USING ARTIFICIAL NEURAL NETWORK BASED ON DATA MINING APPROACHES
Database system has been used in most universities and schools to implement the school information system or also known as academic information system. This database system supports automation of education operationals including capacity planning, courses monitoring, and periodic evaluations. Current school information system can provide operational or transactional report and statistical report. Statistical report is an important information for decision maker to evaluate the current education process and prepare the required strategies to improve its quality. Educational data mining (EDM) is an emerging branch of data mining researches which concerned with developing methods to understand education characteristics, covering students, teacher, study environment, learning substances, and other supporting data. Many researches have been discussed the educational data mining methods for analysing student enrollment, predicting student performance, and predicting student failure. Those methods mine information mainly from school information database system. This research focuses on designing a framework for incorporating business intelligent and data mining on current school information system to improve its functionality as an intelligent education monitoring system. Main entities in education process are observed to determine the required structure to be stored in the database. As a prototype of an implementation of this proposed framework, a prediction of learning output using artificial neural network is observed and tested with the proposed database structure.