Varindya Ditta Iswari , ILKOM UNNES and Florentina Yuni Arini, ILKOM UNNES and Much Aziz Muslim, ILKOM UNNES (2019) Decision Support System for the Selection of Outstanding Students Using the AHP-TOPSIS Combination Method. LONTAR KOMPUTER, 10 (1). pp. 40-48. ISSN 2088-1541

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Abstract

This research develops a decision support system for the selection of outstanding students by combining AHP and TOPSIS methods. AHP method was used because it could be implemented to this data and do the priority ranking process for each criterion based on pairwise comparison matrix. The TOPSIS method was used because the concept of the chosen alternative does not only have the shortest distance from the positive ideal solution, but also has the longest distance from the negative ideal solution. The purpose of this study was finding out the workings of the TOPSIS method and the AHP-TOPSIS combination method, as well as to find out the comparison of the best methods between TOPSIS and the combination method of AHPTOPSIS in the selection of outstanding students. The concept of TOPSIS is simple and easy to understand and has the ability to measure decision alternatives while AHP is not chosen because the AHP method is widely used in the case of criteria weighting and priority determination of each criterion. However, if the two methods were combined the results will be better because in AHP there is an eigenvector concept which is used to do the priority ranking process for each criterion based on pairwise comparison matrix, then the results of the weighting criteria are processed by the TOPSIS method for ranking process. The application of the TOPSIS method on the selection of outstanding students can be analyzed with the results of the presentation using Hamming Distance incompatibility is 93%. Meanwhile, the application of the AHP-TOPSIS combination method gets the presentation results using Hamming Distance incompatibility is 91%. Based on these results in this study it can be concluded that the AHPTOPSIS combination method is better than the TOPSIS method.

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