Prediction of Ship Time in Port Using Machine Learning Algorithm

Simanjuntak, Ronald (Sekolah Tinggi Ilmu Pelayaran Jakarta)
Sibarani, Mauritz (Departemen of KLAK STIP Jakarta)
Cahyadi, Tri (Departemen of KLAK STIP Jakarta)
Sihombing, Derma Watty
Bernadtua, Marudut (Departemen of KLAK STIP Jakarta)

International Journal of Marine Engineering Innovation and Research
Vol 10, No 2 (2025)

The shipping business at the port requires planning in managing time, starting from the ship arrival until the ship leaves the port. Having a prediction or forecast of the ship's time in Port can help the ship's sailing schedule. This research uses machine learning method which is one of the branches of artificial intelligence to predict the time of ships in port for container and general cargo ships where the machine learning algorithm is used to study a set of data and make predictions. Based on the data of arrival time and departure time of ships at Tanjung Priok Port during 2022 and 2023, using Random forrest algorithm, linear regression, KNN regression and SVM, it was obtained that linear regression had mean absolute error, mean squared error, and Root Mean Squared Error more precise than the other algorithms and their determinant coefficients close to one