<![CDATA[This study aims to analyze: 1) the spatial distribution of tourist attractions based on the physical characteristics of the region, 2) the factors influencing tourism object clustering, and 3) the clustering results of tourist attractions in Sawahlunto. This research employed a quantitative method with a spatial approach based on Geographic Information Systems (GIS) and K-Means cluster analysis. The study used secondary data analyzed through several stages, including data collection, data standardization, determination of the number of clusters, clustering process, and interpretation of results. The results show that the spatial distribution of tourist attractions in Sawahlunto is uneven and tends to follow the physical characteristics of areas with good accessibility. The factors influencing the clustering of leading tourist attractions include accessibility level, availability of facilities, number of tourist visits, and characteristics of tourist attractions. The clustering analysis indicates that tourist attractions are divided into two clusters. The first cluster has high criteria supported by good accessibility, infrastructure, and high tourist visits, while the second cluster has lower criteria due to limited accessibility and supporting facilities. This study is expected to serve as a reference for more effective and targeted tourism planning and development.]]>
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