<![CDATA[Tourism is important in economic growth and regional development, especially in East Java Province with diverse tourist attractions. However, the mapping of domestic and foreign tourist visit patterns in this province is still limited. For this reason, this study uses the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method which can group density-based data without determining the number of clusters from the beginning and handle noise. The study aims to map districts/cities in East Java based on the number of tourist visits from 2018 to 2022, using visit data from the East Java Provincial Culture and Tourism Office. The analysis results show that in domestic tourist data, with parameters MinPts = 3 and ε = 1.00, one main cluster is formed consisting of 31 tourist locations and 7 noisy locations. In foreign tourist data, with ε = 0.6 and MinPts = 3, there is one cluster with 30 tourist locations and 8 other locations are categorized as noisy. Noisy locations tend to have higher visits but do not fit into the main cluster. These findings provide important insights for more targeted tourism promotion strategies and efficient resource allocation in East Java.]]>
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