Decision Support System for Determining the Best Coffee Shop Using the Multi Attribute Utility Theory (MAUT) Method with Rank Order Centroid (ROC) Weighting
DOI:
https://doi.org/10.64366/dss.v2i2.94Keywords:
DSS; Coffee Shop; MAUT Method; ROC MethodAbstract
This study discusses the development of a decision support system (DSS) to determine the best coffee shop using the Multi Attribute Utility Theory (MAUT) method and Rank Order Centroid (ROC) weighting. The background of this research is based on the rapid growth of the coffee shop business, which has led to intense competition, requiring business owners to have appropriate strategies and decision-making in choosing a strategic location, adequate facilities, and competitive pricing. The MAUT method is applied because it can accommodate various attributes and criteria that influence decision-making, while ROC is utilized to assign objective weights to each criterion. This study involved five alternative coffee shops, and five evaluation criteria. The results of the calculations show that Coffee Lab achieved the highest final utility value of 0.718, thus being ranked as the best coffee shop, followed by Coffeenatics with 0.395 in second place, Dominico with 0.233 in third place, Kallia with 0.188 in fourth place, and Kopi Tuya with 0.054 in the last position. These findings demonstrate that the application of the MAUT method with ROC weighting can provide objective, systematic, and accurate recommendations in determining the best alternative based on the established criteria. Therefore, this research is expected to serve as a reference for the application of DSS in the coffee shop business sector as well as in other areas that require multi-criteria decision-making.
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