Sains Malaysiana 51(7)(2022): 2305-2314

http://doi.org/10.17576/jsm-2022-5107-29

Pengukuran Risiko menggunakan Rangkaian Bayesan: Aplikasi kepada

Data Perlanggaran Kapal di Malaysia

(Risk Measurement using Bayesian Networks: Applications to Ship Collision Data in Malaysia)

ZAMIRA HASANAH ZAMZURI^1,2,* & ZAIDI ISA^1,2

¹Jabatan Sains Matematik, Fakulti Sains dan Teknologi, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

²Pusat Pemodelan dan Analisis Data, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

Diserahkan: 13 Mac 2022/Diterima: 14 April 2022

Abstrak

Mengenal pasti faktor berbahaya yang mengancam keselamatan adalah penting agar tindakan dapat dirancang untuk menangani akibat jika berlakunya hazard tersebut. Proses pengecaman tersebut memerlukan pengukuran dan komputasi khusus dengan kebarangkalian dan keparahan kejadian tersebut diperlukan. Dalam kajian ini, pendekatan rangkaian Bayesan dilaksanakan untuk menilai, mengenal pasti dan kemudiannya memberi pangkat kepada faktor yang menyumbang kepada berlakunya perlanggaran kapal. Menerusi penggabungan maklumat daripada pandangan pakar dan data lepas, satu rangkaian Bayesan dibina untuk mentafsir kebarangkalian berlakunya perlanggaran diberi pemboleh ubah yang dicerap. Tiga jenis hazard dipertimbangkan dalam kajian ini iaitu teknikal, semula jadi dan kesilapan manusia. Peningkatan dalam kebarangkalian berlakunya perlanggaran kemudiannya dihitung dengan mensyaratkan kepada aras dalam pemboleh ubah dicerap. Tiga faktor pertama yang menyumbang kepada berlakunya perlanggaran kapal adalah kegagalan major dalam sistem komunikasi, kebolehan terjejas tinggi dan ketiadaan pemandu sebagai penasihat pelayaran. Penemuan ini membantu dalam menyerlahkan potensi major ditawarkan oleh rangkaian Bayesan bagi analisis risiko dan penghitungan kebarangkalian. Malahan, kajian ini menawarkan pemahaman yang lebih mendalam kepada pengamal dalam bidang ini untuk merancang atau membina strategi tindakan yang diperlukan bagi mengelakkan berlakunya perlanggaran. Maklumat ini juga penting untuk menilai keselamatan sesuatu kapal dalam usaha mengurangkan potensi suatu perlanggaran tersebut berlaku.

Kata kunci: Bayesan; perlanggaran kapal; rangkaian; risiko

Abstract

Identifying hazardous factors that threaten safety is important so that actions can be planned to address the consequences of the hazard. The identification process requires specific measurements and computations, for which the probability and severity of the event are required. In this study, the Bayesan network approach is implemented to evaluate, identify and then rank the factors that contribute to the occurrence of ship collisions. Through a combination of information from expert views and past data, a Bayesian network was constructed to interpret the probability of a collision given the observed variables. Three types of hazards are considered in this study namely technical, natural, and human error. The increase in the probability of a collision is then calculated by conditional to the level in the observed variable. The first three factors that contribute to the occurrence of shipwrecks are major failures in communication systems, high impaired abilities and the absence of a driver as a navigational advisor. These findings help in highlighting the major potentials offered by the Bayesian network for risk analysis and probability calculations. In fact, this study offers a deeper understanding to practitioners in this field to plan or build the necessary action strategies to avoid the occurrence of collisions. This information is also important in assessing the safety of a ship in an effort to reduce the potential for a collision to occur.

Keywords: Bayesian; network; risk; ship collision

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^*Pengarang untuk surat-menyurat; email: zamira@ukm.edu.my