Integrating AIS Data and Human Error Factors in Optimizing Vessel Navigation Safety in the Mahakam River: A 2024 Incident Case Study

DOI

10.2991/978-94-6239-793-4_4How to use a DOI?

Keywords

Automatic Identification System (AIS); Human error; HFACS; Maritime Safety; Mahakam River; Inland Waterway Navigation

Abstract

This study demonstrates that vessel navigation safety within the Mahakam River is heavily influenced by two primary determinants: the deployment of Automatic Identification System (AIS) technology and human error factors. Through an empirical analysis of three maritime casualties occurring in 2024, combined with a comprehensive literature synthesis, human error was identified as the dominant catalyst contributing to severe accidents, particularly founding vessel capsizings. This finding aligns with the Human Factors Analysis and Classification System (HFACS) framework, underscoring the critical need for risk-based crew training and supervision. Concurrently, AIS plays an essential role in enhancing situational awareness and identifying navigational anomalies, though its restricted utilization among smaller vessels highlights a persistent technological disparity within inland waterways. The core contribution of this research lies in developing an integrative AIS–HFACS framework tailored to tropical river navigation, offering a novel perspective on the dynamic interplay between digital systems and human performance in maritime safety. Theoretically, this study expands the scope of data-driven maritime safety frameworks by incorporating human behavioral dimensions. Practically, it yields policy implications for maritime authorities designing evidence-based training programs, regulatory oversight, and enforcement frameworks. Future research directions should expand the baseline dataset and integrate machine-learning-based HFACS models to refine predictive accuracy and support proactive maritime risk management.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nenny Nenny
AU  - Andi Hasmawati
AU  - Muhammad Yusuf
AU  - Dewi Usabeny
PY  - 2026
DA  - 2026/10/16
TI  - Integrating AIS Data and Human Error Factors in Optimizing Vessel Navigation Safety in the Mahakam River: A 2024 Incident Case Study
BT  - Proceedings of the  International Conference on Advanced Maritime Interconnection (ICAMI 2026)
PB  - Atlantis Press
SP  - 33
EP  - 44
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6239-793-4_4
DO  - 10.2991/978-94-6239-793-4_4
ID  - Nenny2026
ER  -