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Setiawan, Weli Agus
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Social Sciences

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Analyzing the Use of Artificial Intelligence for Optimizing Crewing Management Systems in Indonesian Shipping Companies: A Literature Review Andri Setiawan, Raden Novi; Bintari, Pramudyasari Nur; Ischak, Rabbani; Setiawan, Weli Agus; Octavitri, Yollanda
Journal Of Social Science (JoSS) Vol 4 No 12 (2025): Journal of Social Science
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/djtmp463

Abstract

The shipping industry relies heavily on efficient crewing management to ensure safe vessel operations and compliance with national and international regulations. In Indonesia, crewing management faces persistent challenges, including complex documentation procedures, manual data processing, high administrative workloads, and limited integration between human resource systems and operational platforms. With the rapid expansion of artificial intelligence (AI) technologies, maritime companies increasingly explore AI-based solutions to optimize decision-making, automate routine processes, and enhance overall crew management performance. This study conducts a systematic literature review to analyze the potential, limitations, and implementation models of AI within the context of crewing management systems (CMS). The result shows that AI significantly improves crew scheduling accuracy, reduces administrative workload by up to 40%, enhances regulatory compliance monitoring, and supports predictive analytics for crew performance and turnover. The study concludes that AI-enabled CMS could transform Indonesia’s shipping operations, although challenges remain in terms of digital readiness, data quality, cybersecurity, and regulatory frameworks. Recommendations are provided to support Indonesian shipping companies in adopting AI-driven crewing management solutions
Co-Authors Andri Setiawan, Raden Novi Ischak, Rabbani Pramudyasari Nur Bintari, Pramudyasari Yollanda Octavitri