<![CDATA[The dissemination of information regarding cultural events in Bekasi City has not yet been fully optimized, resulting in uneven public participation across various cultural activities. This issue arises from the absence of a recommendation system capable of suggesting cultural events based on users' interests and preferences. This study aims to implement the User-Based Collaborative Filtering algorithm with the Pearson Correlation approach in a web-based cultural event recommendation system. The research methodology involved observation, interviews, and the collection of user rating data from 100 respondents, with the sample size determined using the Slovin formula. The recommendation process was carried out by calculating the average rating of each user, measuring the similarity between users using the Pearson Correlation coefficient, and predicting ratings for events that had not yet been evaluated by the target user. The results demonstrate that the proposed system is capable of identifying similarities in user preferences and generating personalized event recommendations that align with users' interests. In the case study, the predicted rating for User1 on the Pesta Nada event was 3.76, indicating a high likelihood that the event would be of interest to the user and therefore suitable for recommendation. The implementation of this recommendation system is expected to assist the public in discovering cultural events that match their preferences while supporting the Bekasi City Tourism and Culture Office in disseminating event information more effectively, thereby increasing public participation in cultural activities.]]>
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