<![CDATA[Tourism development in Kalianda District faces the challenge of limited integration among its spatially dispersed attractions, resulting in inefficient tourist movement and uneven visitation patterns. This study aims to analyze the spatial distribution patterns and clustering of tourist attractions as a scientific basis for developing an integrated tourism route. The research employs a quantitative approach based on Geographic Information Systems (GIS), comprising three main analytical methods: the Average Nearest Neighbor (ANN) and Standard Deviational Ellipse (SDE) to determine spatial distribution patterns and directional corridors; Hot Spot (Heatmap) Analysis to identify geographical clusters; and Network Analysis to evaluate accessibility efficiency. The ANN results statistically indicate a Clustered spatial pattern (z-score: -2.58; p-value: 0.009), while the SDE confirms a linear distribution pattern aligned with the coastal corridor. The Hotspot analysis successfully identifies three geographical clusters: one Main Cluster (hotspot) with high density located in the central coastal area, and two Sub-Clusters situated in the northern and southern zones. The Network Analysis demonstrates that the Main Cluster is the most efficiently accessible area from the district’s main entry points (the Kalianda Toll Gate and Bus Terminal). Based on these findings, the study proposes a Cluster-Based Modular Route System strategy, consisting of one Main Route (Kalianda Central Loop) serving the primary hotspot, along with two Alternative Routes—Route A (North) and Route B (South). This modular approach provides greater flexibility for tourists and focuses investment efficiency for local governments, thereby serving as a foundational model for integrated tourism development in Kalianda District]]>
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