EVALUASI PERFORMA SISTEM PENDUKUNG KEPUTUSAN METODE MABAC (STUDI KASUS: PEMILIHAN MAHASIWA BERPRESTASI FMIPA UNIVERSITAS RIAU)

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dc.contributor.authorMasyithah, Dhitha An’nissa
dc.contributor.supervisorId, Ibnu Daqiqil
dc.date.accessioned2024-02-28T02:45:16Z
dc.date.available2024-02-28T02:45:16Z
dc.date.issued2023-11
dc.description.abstractDecision support systems generally apply criteria weighting as an important stage in the resolution process. The method that applies weighting criteria is Multi-Attributive Border Approximation Area Comparison (MABAC). However, the weighting of criteria is mostly done subjectively by the decision maker or team involved. In the case study of selecting outstanding students, there are 10 variations in the weight of the criteria. This makes it difficult to determine the best criteria weight values. Therefore, an evaluation was carried out on the MABAC ranking results based on 10 variations of criteria weights using distance-based methods, namely Manhattan Distance and Euclidean Distance. The method is used to measure the distance between the MABAC ranking and the actual ranking. If the resulting distance is small then the ideal solution can be identified in determining the best weight. The ranking evaluation results of the two methods show that weight 6 has the smallest distance. This means that weight 6 is the best weight because it produces a ranking that is close to the actual rankingen_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alamen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11331
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectDecision Support Systemen_US
dc.subjectEuclidean Distanceen_US
dc.subjectManhattan Distanceen_US
dc.subjectMulti- Attributive Border Approximation Area Comparisonen_US
dc.titleEVALUASI PERFORMA SISTEM PENDUKUNG KEPUTUSAN METODE MABAC (STUDI KASUS: PEMILIHAN MAHASIWA BERPRESTASI FMIPA UNIVERSITAS RIAU)en_US
dc.title.alternativeElfitraen_US
dc.typeArticleen_US

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