Analisis Kecelakaan Kebakaran Dinamik Pada Kamar Mesin Di Kapal Menggunakan Metode Dynamic Bayesian Network

Yasmin, Kayla Andrina (2025) Analisis Kecelakaan Kebakaran Dinamik Pada Kamar Mesin Di Kapal Menggunakan Metode Dynamic Bayesian Network. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini bertujuan untuk menganalisis faktor-faktor penyebab dan yang memengaruhi kebakaran di kamar mesin kapal menggunakan pendekatan Dynamic Bayesian Network (DBN). Data yang digunakan bersumber dari 22 laporan kecelakaan kebakaran ruang mesin yang diperoleh dari investigasi KNKT dan putusan Mahkamah Pelayaran, serta dilengkapi dengan referensi dari studi literatur untuk mengidentifikasi faktor-faktor potensial lainnya. Hasil identifikasi menghasilkan 30 node factor yang disusun ke dalam model DBN dengan mempertimbangkan tiga time step berdasarkan tahapan kurva pertumbuhan kebakaran: awal kebakaran muncul, fase kebakaran berkembang, dan fase kebakaran mulai mereda. Probabilitas awal (prior), bersyarat (conditional), gabungan (joint), dan posterior dihitung untuk mengevaluasi bagaimana masing-masing faktor mempengaruhi kebakaran secara dinamis. Hasil analisis menunjukkan bahwa Crew Decision dan Portable Fire Fighting System merupakan faktor paling krusial yang mempengaruhi keberhasilan pengendalian kebakaran, terutama pada tahap awal kejadian. Model juga menunjukkan bahwa gangguan pada sistem kelistrikan dan kerusakan komponen mesin merupakan penyebab utama dari kebakaran berdasarkan data historis. Evaluasi strength of influence mengonfirmasi bahwa sistem sirkulasi serta sistem elektrikal mempunyai hubungan yang paling kuat dengan node penyusunnya. Penelitian ini menegaskan pentingnya kesiapan tanggap darurat awak kapal dan efektivitas sistem deteksi serta pemadaman kebakaran pada tahap awal insiden. Selain itu, hasil model selaras dengan kejadian faktual di lapangan dan mendukung rekomendasi untuk peningkatan kompetensi kru sesuai regulasi STCW serta penerapan fire drill secara rutin sebagaimana diatur dalam SOLAS dan FFS Code.
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This study aims to analyze the causes and influencing factors of engine room fires on ships using the Dynamic Bayesian Network (DBN) approach. The analysis is based on 22 historical engine room fire incidents documented in investigation reports by the National Transportation Safety Committee (KNKT) and maritime court decisions in Indonesia, complemented by literature studies to include additional potential risk factors. A total of 30 node factors were identified and structured into a DBN model with three time steps corresponding to fire development stages: ignition, fully developed fire, and decay. Prior, conditional, joint, and posterior probabilities were calculated to evaluate how each factor dynamically influences the development of fire incidents. The analysis revealed that Crew Decision and the Portable Fire Fighting System (PFFS) are the most critical variables affecting fire containment, especially during the initial fire stage. Data also indicated that most fires were triggered by electrical issues and mechanical component failures. The strength of influence analysis confirmed that the circulation systems and electrical systems have the strongest influence with their parent nodes. This study highlights the critical importance of crew response and early firefighting efforts in managing engine room fires. The model aligns with real-world case studies and supports recommendations to improve crew competence in line with the STCW convention and enforce regular fire drills as required by SOLAS and the FFS Code.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Dynamic Bayesian Network, Kebakaran Kamar Mesin, Probabilitas Kebakaran, Keselamatan Kapal, GeNIe, Engine Room Fire, Fire Probability, Ship Safety
Subjects:	T Technology > T Technology (General) > T174.5 Technology--Risk assessment. T Technology > TA Engineering (General). Civil engineering (General) > TA169.5 Failure analysis V Naval Science > VK > VK1258 Ships--Fires and fire prevention V Naval Science > VK > VK200 Merchant marine--Safety measures
Divisions:	Faculty of Marine Technology (MARTECH) > Marine Engineering > 36202-(S1) Undergraduate Thesis
Depositing User:	Kayla Andrina Yasmin
Date Deposited:	04 Aug 2025 01:28
Last Modified:	20 Aug 2025 01:59
URI:	http://repository.its.ac.id/id/eprint/126483

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