Intelligent higher institution student selection system

Higher education institutions admission faces the need for a precise and effective method to evaluate and select the most qualified applicants to be in their institution. Currently, admission officers have to manually evaluate every applicant's data against the set of admission requirements before selecting the few successful ones. The manual process contributes many problems such as inaccurate decision resulting from human error, needs a lot of effort and is time consuming. The objectives of the paper is to identify and suggest an intelligent selection method using fuzzy system to assist higher institutions to select the most suitable applicants and also suggest suitable course based on their high school certificate result. There are two phases involved in this project. The first phase requires user to input the data which will be processed in the fuzzy inference system. If the applicant qualifies, the system will proceed to the second phase which is course suggestion phase. The result shows whether the applicant qualify and if so, will be suggested a course. This project uses Suge-no-Style Fuzzy Inference technique to select the suitable applicants. A prototype was developed and tested with thirty sample data. From the analysis, this prototype achieved 83% accuracy. As a conclusion, this technique is suitable to be applied to automatically suggest suitable applicants for intake into higher institutions.