<![CDATA[Yogyakarta is one of the leading tourist destinations in Indonesia with diverse attractions, ranging from cultural, historical, to natural attrac-tions, which often pose challenges for tourists in determining tourist destinations according to their preferences. This study aims to develop a recommendation system for the best tourist destinations in Yogya-karta City through the integration of the Multifactor Evaluation Pro-cess (MFEP) and K-Means Clustering methods. MFEP is used to rank destinations based on five main criteria, namely location, accessibility, facilities, cost, and uniqueness, with weights obtained from the results of tourist preference surveys. The ranking results are then analyzed using K-Means Clustering to group destinations into three categories of tourism potential, namely high, medium, and low, based on addi-tional parameters such as strategic location, number of attractions, and number of visitors. The results of this study prove that the integration of MFEP and K-Means is able to produce fast, accurate, and informa-tive recommendations, and can be used by tourists and tourism manag-ers in strategic planning and decision-making. System functionality testing using the black box method shows that all features run as need-ed, while clustering quality testing using the Silhouette Coefficient method produces very good clustering quality with an average score of 0.9552.]]>
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