Optimalisasi Pemeliharaan Permesinan Kapal Berbasis Artificial Intelligence sesuai Peraturan Pemerintah No. 31 Tahun 2021 tentang Penyelenggaraan Bidang Pelayaran

Aris Sarjito

doi:10.52475/saintara.v9i1.368

Aris Sarjito Universitas Pertahanan Republik Indonesia, Jakarta

DOI: https://doi.org/10.52475/saintara.v9i1.368

Keywords: Artificial Intelligence, Fuel Efficiency, Predictive Maintenance, Ship Safety

Abstract

The application of artificial intelligence (AI) technology in ship machinery maintenance has become a potential solution to improve operational efficiency and safety, especially in the Indonesian maritime industry, which is facing high cost and safety challenges. This study aims to develop an AI-based predictive maintenance method following Government Regulation No. 31 of 2021 concerning shipping implementation, emphasizing the importance of safety and sustainability in ship operations. This study uses a qualitative approach with secondary data, including government documents, industry reports, and academic literature on predictive maintenance and energy efficiency in ship machinery. Through thematic analysis of secondary data, the study found that the application of AI in predictive maintenance can detect potential damage early, optimize fuel use, and reduce emissions. In addition, the study results show that using AI significantly reduces operational costs and increases compliance with safety standards stipulated in government regulations. The conclusion of this study states that AI-based ship machinery maintenance not only supports environmental efficiency and sustainability but also ensures safer ship operations and following applicable regulations. Implementing this AI technology is expected to encourage the Indonesian shipping industry to be more competitive regarding sustainability and safety.

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