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All Journal International Journal of Marine Engineering Innovation and Research
Fanny Octaviani
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Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation

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Automatic Identification System (AIS) Data Reliability and Its Implications for Maritime Safety in Indonesia Mohammad Danil Arifin; Muswar Muslim; Fanny Octaviani; Danny Faturachman
International Journal of Marine Engineering Innovation and Research Vol. 10 No. 3 (2025)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v10i3

Abstract

The Automatic Identification System (AIS) is central to vessel monitoring, traffic management, and maritime safety, yet concerns remain regarding its reliability due to incomplete, inaccurate, or delayed reporting. This study assesses AIS data from the Indonesian maritime domain, focusing on four parameters: completeness, accuracy, consistency, and timeliness. AIS records data were preprocessed through data cleaning, filtering, and detection of missing values in static fields such as draught, beam, LOA, deadweight, and gross tonnage (GT). Statistical and spatial-temporal analyses using Python were applied to quantify missing data, identify anomalies, and evaluate reporting intervals. Results show high completeness (97.5%), although missing draught data (6.77%) limited under-keel clearance assessments, while small gaps in beam and LOA affected collision risk modeling and berth allocation. Accuracy was moderate, with invalid speed and course records observed, whereas consistency was excellent, with MMSI and ship names fully aligned. Timeliness proved weakest, with median reporting intervals (8,380 seconds) exceeding IMO standards, restricting real-time navigational use but remaining suitable for long-term monitoring. Overall, AIS in Indonesia is reliable for strategic traffic analysis but insufficient for operational safety management. Strengthening reporting compliance, integrating port and registry databases, and applying anomaly detection and satellite AIS are recommended to enhance maritime safety.
Analysis of Causes and Impacts of Tug and Barge Vessel Accidents Using the Analytic Hierarchy Process: A Case Study of XYZ Company Danil Arifin, Mohammad; Mohammad Fajar Sodiq; Aldyn Clinton Partahi Oloan; Y. Arya Dewanto; Fanny Octaviani
International Journal of Marine Engineering Innovation and Research Vol. 11 No. 1 (2026)
Publisher : Department of Marine Engineering, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j25481479.v11i1

Abstract

Indonesia’s maritime sector plays a strategic role in national logistics, where tug and barge vessels are widely used to transport bulk commodities due to their cost efficiency and operational flexibility. However, tug and barge operations face a high risk of accidents, particularly in densely trafficked waterways and challenging environmental conditions. This study aims to analyze the causes and impacts of tug and barge vessel accidents at Company XYZ during the period 2015–2024 and to determine priority mitigation measures using the Analytic Hierarchy Process (AHP). The study analyzes 170 recorded accident cases classified into human, technical, environmental, and procedural factors. The results show that human factors are the dominant cause, contributing 55.8% of accidents, followed by technical factors (26.3%), environmental factors (12.2%), and procedural factors (5.7%). The accidents resulted in material losses, operational delays of 3–7 days per incident, and environmental impacts such as fuel spills and onboard fires. The AHP results indicate that human-related factors are the highest priority for mitigation, followed by technical, environmental, and procedural factors, with a consistency ratio of 0.043, indicating acceptable reliability. This study provides a structured decision-making approach to support safety improvement and risk mitigation in tug and barge vessel operations.
Co-Authors Aldyn Clinton Partahi Oloan Danny Faturachman Mohammad Danil Arifin Mohammad Fajar Sodiq Muswar Muslim Y. Arya Dewanto