Multi Attribute Decision Making Penentuan Dosen Terbaik Menggunakan Metode Multi-Objective Optimization by Ratio Analysis dan Surrogate Weighting
Abstract
The best lecturers are people who not only have high academic expertise in their fields, but also have the ability to inspire and guide students well. The main problem in determining the best lecturer is subjectivity in the evaluation process. Evaluation of lecturer performance often tends to be based on parameters that are qualitative in nature and can be influenced by personal preferences, or subjective perceptions. This study aims to solve problems in the selection of the best lecturers using the MADM approach with the method used, namely MOORA in the selection of the best lecturers and the surrogate weighting method to determine the weight of criteria to be used in the selection of the best lecturers. The ranking results show no difference in ranking from the rank sum, rank order centroid, and reciprocal rank weighting methods. The results for rank 1 were obtained on behalf of ID Lecturers, rank 3 was obtained on behalf of SH Lecturers, and rank 3 was obtained on behalf of KU Lecturers, using the rank sum, rank order centroid, and rank reciprocal weighting methods. The comparison results that the rank sum, rank order centroid, and reciprocal rank weighting methods are very suitable in recommending the best lecturers by applying the MOORA method. The combination of rank sum weighting method and MOORA, the combination of rank order centroid and MOORA weighting method, and the combination of reciprocal rank weighting method and MOORA there is no difference in the final ranking of the best lecturers.
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References
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