This study analyzes Automatic Identification System (AIS) data collected by the AIS-POLBENG Remote Base Station (RBS) in the Malacca Strait over a five-month period (February–June 2025) to support maritime traffic monitoring. The AIS data processing system was developed to encompass raw data recording, data cleaning and transformation, information extraction, data visualization and analysis. By utilizing open-source technologies such as PyAIS and PostgreSQL integrated with Python in Jupyter Notebook, the research generates strategic insights including vessel flag-state distribution, vessel types, navigational status, and traffic density. The analysis reveals that maritime traffic is dominated by foreign-flagged vessels, particularly those from Panama, Singapore, and the Marshall Islands, with cargo ships (54.49%) and tankers (24.02%) as the predominant vessel types. Most vessels were in the UnderWayUsingEngine status (84.88%), indicating high levels of engine-powered navigation activity. The average traffic density was recorded at 1.36 vessels/km2 per month, totaling 6.83 vessels/km2 during the observation period. These findings reaffirm the Malacca Strait as a high-intensity strategic shipping lane, underscoring the need for optimal traffic management to ensure navigational safety and efficiency.