<![CDATA[This study explores the integration of Artificial Intelligence (AI) and Big Data in mapping geographical keywords related to tourism destinations in Indonesia. Using an exploratory qualitative approach, the study aims to understand how tourism-related keyword search behavior can reveal regional tourism trends, thematic interests of travelers, and seasonal dynamics of tourism demand. Data were collected from tourism keyword searches throughout 2023–2024 and analyzed using Natural Language Processing (NLP) techniques, including thematic classification, semantic mapping, and keyword association analysis. The findings reveal four key insights: (1) the frequency of geographical keywords highlights both popular and emerging tourism areas; (2) thematic classification identifies traveler interests in cultural, natural, and culinary tourism; (3) temporal analysis shows consistent seasonal patterns in search intensity; and (4) semantic mapping displays relationships among keywords, reflecting traveler perceptions and preferences. The study emphasizes that AI and Big Data can enhance destination branding, policy planning, and personalized tourism marketing strategies. In addition to contributing theoretically to the smart tourism literature, it also offers practical guidance for stakeholders to align promotional strategies with actual search trends and regional tourism needs.]]>
Copyrights © 2025
