TRAVEL ITINERARY RECOMMENDER SYSTEM USING MACHINE LEARNING ANALYSIS AND WEB APPLICATION DEVELOPMENT: A CASE OF BATAM CITY REGION - Hosse Fernando; Syaeful Anas Aklani (JURNAL ILMIAH BETRIK, 2023)
Batam City is an island with a complete and diverse point of destination (POI). Searching for information is common when someone is making a travel itinerary. With the help of technology, planning a trip should be fast and easy. In this study, the authors will build a web application-based recommender system with the help of machine learning. This study uses the ADDIE (Analysis, Design, Development, Implementation, Evaluation) development method and then the TAM Model (Technology Acceptance Model) to analyze the effectiveness. The results of system testing show a range of scores with the lowest value 0.509 and the highest value 0.572. This score indicates the degree of correlation between the test and the underlying construct it is designed to measure. A score of 0.509 indicates a weak correlation between the test and constructs, while a score of 0.572 indicates a stronger correlation. Score above 0.5 Thus, the authors hope that this research can be used as a reference or knowledge for future readers or researchers.