WITHDRAWN: Intelligent system for graduation projects allocation based on MCDA methods

Abstract

The graduation projects are an important part of the educational activity for each student for obtaining the graduation certificate in the higher education environment, it contributes to developing the student's personal, academic and professional skills. Getting an optimal project allocation considered a major problem in any university since it directly affects the quality of the completed projects and ensuring achieve the greatest scientific benefit for each student. This paper presents a novel strategy for allocation projects based on the students’ progress data in the previous six semesters. By employing the pre-processing technique (i.e. data wrangling) to extract the important information for each student. The integrated MCDA algorithms are adopted (i.e. Integrated Entropy- TOPSIS methods) to deal with that pre-processed information and make a decision to allocate an appropriate project for each student. The new allocation strategy addresses many of the problems that appeared in the previous allocation strategies, like the problems of random allocation, workload balancing for each supervisor, unallocated student problem…etc. the proposed system implemented for real dataset to determine the SFs prioritization in business informatics college. All the ranking SFs results were validate tested with an overall score of 100%.