Mining College Admission Data in Syria (Journal of Hama University, 2021)
It is clear to everyone that the College admission process is a strategic process at the country level, and is very important for citizens of all categories. This process receives attention from all divisions of society, students, their families and the educational sector in general, so it was necessary to pay attention to the smallest details, and try to improve and simplify it. The Directorate of Information and Communications Technology in the Ministry of Higher Education and Scientific Research in Syria adopts the announcements issued by the ministry to implement trade-offs electronically, and these announcements are considered as the regulator for the work of software programs. This study aimed to employ college admission data for the scientific branch gathered during the previous ten years, and use it to create a predictive model that applies to new students coming to college admission. The most important results of the study were:Designing a predictive model using the WEKA workbench for data mining, using the college admission data gathered during the previous ten years, and apply it to students of the scientific branch coming to college admission. This model is used to guide students to the university and the appropriate college for them, according to their data, and using the model for decision support in the Ministry of Higher Education and Scientific Research to contribute to assign the appropriate seats for colleges and institutes in all Syrian Governmental universities, before starting college admission process.
Keywords: Data Mining; Weka Workbench; College Admission; Decision Trees; Naïve Bayes; Nearest Neighbor; Class Attribute; Prediction; Classification; Attribute Selection