<![CDATA[The Bali Strait is one of the busiest sea crossing routes in Indonesia, characterized by high intensity of ship movements and dynamic traffic patterns throughout the day. These conditions require comprehensive analysis to understand the characteristics of vessel movements, identify density zones, and determine peak periods that potentially increase navigation risks. This study aims to analyze ship traffic patterns in the Bali Strait using a combination of K-Means Clustering and Traffic Flow Model based on Automatic Identification System (AIS) data. The dataset consists of 790 AIS records collected during the period of 20–26 June 2025. The research stages include data preprocessing, determination of the optimal number of clusters using the Elbow method, classification of vessel movement behavior using the K-Means algorithm, and analysis of traffic parameters comprising volume, speed, density, and traffic flow. The results reveal the formation of three main clusters: low-speed vessels concentrated around port areas, medium-speed vessels operating on main trajectories, and high-speed vessels dominating the crossing lanes. Evaluation of clustering quality using the Silhouette Coefficient produced a value of 0.3040, indicating a reasonably good level of cluster separation. Furthermore, a consistent peak hour pattern was identified at 12:00, along with two high-density zones located near Ketapang Port and Gilimanuk Port. These findings demonstrate that AIS-based analysis is capable of providing measurable representation of the dynamics of ship traffic in the Bali Strait and has the potential to support operational optimization, enhancement of navigation safety, and consideration for the implementation of a Traffic Separation Scheme (TSS)]]>
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