Optimizing ship guidance service time based on movement order fluctuations: An applied nonlinear analytics and Markov chain analysis approach

Ship piloting services at ports are crucial for ensuring safety and efficiency. This process requires pilots to control ships by considering various dynamic factors such as wind, currents, and environmental conditions. This research aims to optimize guiding service time based on fluctuations in movement commands issued by guides. Using Markov Chain analysis, this study examines MV ship movement command data during simulation training at the Semarang Seafaring Science Polytechnic. The results demonstrate that the Markov Chain method effectively identifies movement command patterns and the duration needed to achieve "finish with engine" (FWE). Consequently, this research establishes a standard for pilot service times that can serve as a reference for evaluating pilot competency and optimizing port resources. In conclusion, this analysis can support improvements in the quality of safe and efficient pilotage services at ports.