<![CDATA[Bogor has many tourist destination options with diverse characteristics that often make tourists difficult to determine destinations according to their preferences. Therefore, a system is needed to assist tourists in making decisions effectively. This research implements a web-based Decision Support System to provide recommendations for tourist destinations in Bogor using the User-Based Collaborative Filtering method with cosine similarity. The system is developed using Python and Flask framework, analyzing similarity patterns of ratings between users to generate personal recommendations. The collaborative filtering method works by identifying users who have similar preferences, then recommending tourist destinations that are favored by users with similar preference characteristics. System performance evaluation using RMSE and MAE metrics shows a good level of prediction accuracy. This system helps tourists obtain more personalized and efficient recommendations, and can be utilized by tourism managers as a data-driven promotional tool. The implementation of this system is expected to improve tourist experience in choosing destinations and support the development of the tourism sector in Bogor]]>
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