Devi, Firda Puspita (2017) Implementasi Bayesian Network Untuk Perhitungan Probabilitas Pada Penilaian Risiko Pipa Bawah Laut Oleh Faktor Kapal. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penyaluran minyak dan gas bumi dengan pipa bawah laut sangat efisien karena memerlukan biaya yang minimal. Namun, seiring padatnya aktivitas maritim oleh lalu lintas kapal akan berdampak kerusakan pada jaringan pipa bawah laut. Penyebab kerusakan tersebut dapat disebabkan oleh beberapa faktor, antara lain: jatuhnya jangkar kapal (anchor drop), kapal tenggelam akibat gagal mesin, jaring atau pukat (trawl), dan faktor lainnya. Oleh karena itu, penilaian risiko untuk kapal yang melewati jaringan pipa bawah laut sangat diperlukan. Pada penelitian ini, metode Bayesian Network (BN) digunakan untuk memodelkan penyebab kecelakaan pipa bawah laut oleh faktor kapal dan menghitung probabilitas kerusakan yang ditimbulkannya. Adapun standar DNV RP F107 digunakan untuk mengklasifikasi tingkat risiko berdasarkan nilai probabilitas yang didapat. Hasil pengujian program ini menunjukkan bahwa 58.4% kemungkinan kapal yang lewat tidak menyebabkan kerusakan pada pipa, 13.83% kerusakan yang ditimbulkan kecil, 15.14% kerusakan yang ditimbulkan menengah, dan 12.59% kerusakan yang ditimbulkan besar.====================================================================================================The transportation of hydrocarbon by subsea pipeline is highly efficient while requiring minimal cost. However, with the rapid extention of offshore pipeline and the increasing of maritime activities, it can be reasonably expected that accident to offshore pipeline. Some hazards include anchor drop, drowing ship as a consequence to failed engine, trawl, etc. Hence the risk management is thus necessary with passing ship, which can be categorized as damage to offshore pipeline by “ship factors”. In this paper, Bayesian Network (BN) model are proposed to present a broad range of accident scenarios and determine final probabilities of anchor damage and trawling damage to subsea pipeline. In addition, DNV RP F107 is used to classify risk ranking according to the probability. As a result, 58.4% of ships passing isn’t impact to pipeline damage, the 1st segment the percentage is 13.83% (low probability), the 2st segment the percentage is 15.14% (moderate), and the 3rd the percentage is 12.59% (major).
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Pipa Bawah laut; Probabilitas; Bayesian Network; DNV RP F107; Subsea Pipeline; Probability |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science. EDP |
| Divisions: | Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | - FIRDA PUSPITA DEVI |
| Date Deposited: | 24 Mar 2017 09:23 |
| Last Modified: | 24 Mar 2017 09:23 |
| URI: | http://repository.its.ac.id/id/eprint/3237 |
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