Application of Collaborative Filtering Method to Recommend Tourist Destinations in Jakarta City

The new approach in recommending the places to visit in Jakarta City is by collaborative filtering. In this research, reviews and ratings of 437 users from TripAdvisor, Traveloka, and Booking.com are used. This methodology will be multifaceted, with user-based and item-based collaborative filtering techniques, as well as deep learning for enhanced personalization. Content-Based Filtering will also be implemented in this methodology. Results indicate that the system is viable in personalization of recommendations to tourists for better experiences and high engagement rates with local business entities. This research puts into context the challenges of real-time implementation and gives a way forward for future work toward improving the Recommendation System. The findings bring out significant implications for Jakarta's tourism sector in ensuring efficient and enjoyable travel experiences.