Analisis Pengambilan Keputusan Dalam Pemilihan Metode Decommissioning dengan Bayesian Network Pada Platform Lepas Pantai

Wardana, Zahra Ramadhani (2025) Analisis Pengambilan Keputusan Dalam Pemilihan Metode Decommissioning dengan Bayesian Network Pada Platform Lepas Pantai. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Industri minyak dan gas lepas pantai di Indonesia menghadapi tantangan signifikan dalam mengelola proses decommissioning platform yang telah melampaui masa operasionalnya. Data menunjukkan bahwa lebih dari 50% platform offshore berusia di atas 20 tahun, sehingga diperlukan pendekatan yang sistematis dan berbasis data untuk menentukan metode decommissioning yang paling optimal. Pemilihan metode ini tidak sederhana, karena melibatkan berbagai faktor teknis, ekonomi, lingkungan, dan regulasi, serta dipengaruhi oleh tingkat ketidakpastian dalam hal biaya dan risiko. Saat ini, metode yang umum digunakan mencakup Complete Removal, Partial Removal, dan Toppling, yang masing-masing memiliki keunggulan dan konsekuensi tersendiri. Penelitian ini bertujuan untuk mengembangkan model Bayesian Network sebagai alat bantu pengambilan keputusan yang mampu mengakomodasi ketidakpastian dalam pemilihan metode decommissioning untuk struktur jacket platform lepas pantai. Data diperoleh melalui studi literatur dan wawancara dengan para ahli industri minyak dan gas. Model kemudian divalidasi melalui studi kasus Platform A. Hasil simulasi menunjukkan bahwa metode Complete Removal merupakan alternatif paling optimal dengan probabilitas sebesar 78%. Rekomendasi model ini konsisten dengan engineering judgement dari studi kasus aktual. Validasi dari para expert juga menunjukkan bahwa model ini dapat diterapkan dan mampu merepresentasikan proses pengambilan keputusan secara logis dan relevan.
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Indonesia’s offshore oil and gas industry faces significant challenges in managing the decommissioning of platforms that have exceeded their operational lifespans. Data indicate that over 50% of offshore platforms in Indonesian waters are more than 20 years old, highlighting the urgent need for a systematic and data-driven approach to determine the most appropriate decommissioning method. This decision-making process is complex, as it involves a wide range of interrelated technical, economic, environmental, and regulatory factors, all of which are subject to uncertainty in terms of cost and operational risk. Currently, the commonly adopted decommissioning methods include Complete Removal, Partial Removal, and Toppling, each with distinct advantages and trade-offs. This study aims to develop a Bayesian Network (BN) model as a decision-support tool that can accommodate uncertainty in selecting the optimal decommissioning method for fixed offshore jacket platforms. Data for model development were obtained through comprehensive literature review and expert interviews within the oil and gas industry. The model was subsequently validated using a case study of Platform A.
Simulation results indicate that the Complete Removal method is the most optimal alternative, with a probability of 78%. The model’s recommendations align with the engineering judgment applied in the actual case study. Expert validation further confirms that the proposed model is applicable and capable of logically and reliably representing the decision-making process.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Bayesian Network, Decommissioning, Ketidakpastian, Pengambilan Keputusan, Platform Lepas Pantai ============================================================ Bayesian Network, Decommissioning, Uncertainty, Decision-Making, Offshore Platform
Subjects:	T Technology > TH Building construction > TH438 Construction industry--Management. Project management.
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Civil Engineering > 22101-(S2) Master Thesis
Depositing User:	Zahra Ramadhani Wardana
Date Deposited:	28 Jul 2025 08:47
Last Modified:	28 Jul 2025 08:47
URI:	http://repository.its.ac.id/id/eprint/122778

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