<![CDATA[Tourism plays a vital role in Indonesia’s regional development, yet spatial disparities in tourism performance remain evident across East Nusa Tenggara (NTT). This study examines multidimensional tourism performance by integrating indicators of market demand, supply effectiveness, economic impact, and accessibility. The research addresses the problem of unequal regional tourism performance and asks: How can statistical clustering identify performance disparities among NTT’s districts? The novelty of this study lies in applying unsupervised learning (K-Means clustering) at the district/city level, combining UMAP for dimensionality reduction and dual validation using the Silhouette Score and Adjusted Rand Index (ARI). The study employs standardized secondary data (2021–2024) from Statistics Indonesia, analyzed using R 4.5.1. Results show that the optimal number of clusters is three, with a Silhouette Score of 0.472 (moderate structure) and ARI of 0.813 (excellent recovery). Cluster 1 represents high-performing regions with superior accessibility and demand, Cluster 2 reflects transitional areas with strong capacity but weak utilization, and Cluster 3 includes underperforming regions. Centroid analysis reveals external access and market demand as key differentiators, providing an empirical basis for targeted tourism policy in NTT.]]>
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