Big Data and GIS Integration for Tourism Potential Mapping

Case Study of Sinjai Regency, Indonesia

Abstract

This study aims to integrate Big Data analysis through Google Trends with spatial mapping using Geographic Information Systems (GIS) to identify and map tourism potential in Sinjai Regency, Indonesia. Google Trends data is used to search for tourist destinations that are dominant in public searches, while tourist visit data from official local government reports is analyzed to strengthen the validity of the findings. The results of the analysis show that marine destinations such as Marannu Beach, Mallenreng Beach, and Tongke-Tongke Mangrove Forest have high search and visit rates, indicating great potential for the development of marine-based tourism. Meanwhile, natural attractions such as Fafaliang Water Park, Bulu Lanceng, and Kampoeng Galung also showed significant contributions in attracting tourists. The integration of Google Trends data with actual visit data through GIS produces a distribution map that illustrates the spatial dominance of each travel category, while revealing the relationship between accessibility and visit intensity. These findings contribute to the strategic planning of sustainable tourism in the region by taking into account digitally recorded public preferences as well as empirical data from the field. This study emphasizes the importance of the use of Big Data and geospatial technology to strengthen tourism destination development policies at the local level.