<![CDATA[Hydrometeorological disasters, such as flooding by seawater intrusion and land subsidence from excessive water resource usage, significantly disrupt maritime traffic and port infrastructure, leading to severe economic and social consequences. This study aims to develop a conceptual model for a disaster-resilient and environmentally friendly port. The primary objective is to analyze the components of the Port Masterplan (RIP), the Greenport concept, current operational conditions, and surrounding disaster threats for develop conceptual model. A mixed-methods approach, integrating quantitative and qualitative analyses, was employed. The study examined various components of the Tanjung Priok Port Masterplan, operational data, and environmental and disaster risk assessments. Observational methods involved a detailed analysis of current port operations and infrastructure, while analytical methods included Bayesian network analysis facilitated by Genie for Academic software. The primary outcomes were measured in terms of the port’s resilience and environmental friendliness, measured using Conditional Probability Table (CPT) values. This study highlights the need for integrating environmental sustainability and disaster management variables into the Tanjung Priok Port Masterplan. Notably, the study introduces two key innovations: the application of the Greenport concept and the use of Bayesian network analysis to identify causal relationships among critical variables. By incorporating these elements, the Port Masterplan can be strengthened, to ensure the sustainable and resilient development and operation of the Tanjung Priok Port. The Bayesian Network analysis revealed a strong causal relationship among the variables, indicating that the current Masterplan insufficiently addresses disaster preparedness, Specifically, the CPT values showing that only 36% of the port’s operations can be classified as resilience and environmental friendliness, while the remaining 64% fall under non-resilience and non- environmental friendliness categories.]]>
