Pengembangan Sistem Informasi Rekomendasi Wisata Kalimatan Timur Berbasis Web Menggunakan Metode Item-Based Collaborative Filtering

Abstract

The development of a tourism object is an important sector in the development of an area to support the economic power of the people in the area, this also applies to the East Kalimantan province. In order to improve the tourist experience, the development of a tourist recommendation information system is a necessity. This research discusses the development of a web-based Tourism Recommendation Information System and Tourism Chatbot specifically for East Kalimantan Province.Item-Based Collaborative Filtering method is implemented in the development of this system. This method utilizes historical data of user preferences to recommend suitable tourist destinations. The data collected includes user preferences for various attractions, such as location, facilities, and types of activities. The development process starts from data collection and processing, building a web information system, to integration with a chatbot.Tourist Recommendation Information System provides recommendations for tourist destinations tailored to user preferences. Through a user-friendly web interface, users can explore interactive maps, find out the details of attractions, and see reviews from previous visitors. In addition, the Tourism Chatbot provides real-time information and recommendation services to users through an instant messaging platform. The trial results show that the Item-Based Collaborative Filtering method is able to provide recommendations that are relevant to user preferences. Users feel more assisted in planning their travel trips. The system also succeeded in increasing user interaction and engagement through the use of a responsive chatbot.In conclusion, the development of a web-based Tourism Recommendation Information System and Tourism Chatbot with the Item-Based Collaborative Filtering method can be an effective solution in improving the tourist experience in East Kalimantan Province. This system provides accurate recommendations and empowers users to plan a better and memorable tour.