Seasonal Forecasting of Ferry Passenger Demand for Operational Planning: Evidence from Bakauheni Port, Indonesia - Abdullah, Khoirul Mizan; Muthoharoh, Luluk; Satria, Eggie; Neliyana, Rahma; Presilia, Presilia; Khoarizmy, Gymnastiar Al; Muslim, Anwar; Safitri, Ira (Universitas Islam Negeri Raden Intan Lampung, Indonesia, 2025)
Forecasting ferry passenger numbers is essential for efficient port operations and resource planning. This study applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) model to forecast monthly passenger volumes at Bakauheni Port, Lampung. The SARIMA (2,1,1)(0,1,1)₁₂ model was selected for its ability to capture trend and seasonal patterns effectively. Diagnostic checks confirmed the model's adequacy, and validation yielded a MAPE of 11.47 percent, indicating 88.53 percent accuracy. These results show that the SARIMA model offers reliable predictive performance and can support data-driven decisions in scheduling, resource allocation, and service optimization. These results demonstrate that the developed SARIMA model possesses reliable predictive performance and can serve as a practical tool for supporting operational decision-making. The model can help this port authorities and managers optimize service provision, allocate resources more efficiently, and respond proactively to anticipated changes in passenger volume, thereby improving overall port performance and customer satisfaction in the future. Although it does not incorporate external factors, the model provides a solid foundation for future improvements and research.