Cost overrun merupakan permasalahan yang konsisten terjadi pada proyek konstruksi berskala besar di seluruh dunia, termasuk pada proyek pembangkit listrik. Salah satu proyek PLTGU di Indonesia terbukti mengalami pembengkakan biaya sebagaimana tercatat dalam laporan resmi konsultan pengawas. Penelitian ini bertujuan untuk mengetahui nilai probabilitas tertinggi faktor penyebab cost overrun, mengidentifikasi faktor-faktor dalam Minimal Cut Set (MCS), serta menentukan faktor paling dominan berdasarkan Fussell-Vesely Importance Measure (IFV). Data primer diperoleh melalui kuesioner skala Likert 1–5 yang disebarkan kepada responden ahli yang dipilih secara purposive sampling, meliputi Project Manager, Site Engineer, QC Engineer, konsultan pengawas, dan pelaksana lapangan yang terlibat langsung dalam proyek. Analisis dilakukan menggunakan metode Fault Tree Analysis (FTA) kuantitatif dengan tahapan konversi probabilitas, penyusunan diagram FTA, analisis MCS, perhitungan probabilitas top event, dan pengukuran IFV. Hasil penelitian menunjukkan bahwa nilai probabilitas tertinggi diperoleh oleh X23 (Cuaca buruk) dan X26 (Gangguan masyarakat sekitar) dengan P = 0,700. Analisis Minimal Cut Set (MCS) menghasilkan 21 MCS yang terdiri dari 12 MCS orde-1 dan 9 MCS orde-2, dengan probabilitas top event sebesar P(T) = 0,9996. Faktor paling dominan berdasarkan IFV adalah X23 (Cuaca buruk) dengan IFV = 0,7003, diikuti X24 (Perubahan regulasi pemerintah) dengan IFV = 0,5502, yang menunjukkan dominasi faktor eksternal terhadap risiko cost overrun pada proyek ini. Hasil penelitian ini diharapkan dapat memberikan rekomendasi pengendalian biaya bagi para pemangku kepentingan pada proyek pembangkit listrik serupa di Indonesia.

Cost overrun is a persistent problem in large-scale construction projects worldwide, including power plant projects. One PLTGU project in Indonesia was found to experience cost overrun as recorded in the official supervisory consultant's report. This study aims to determine the highest probability value of cost overrun causative factors, identify factors included in the Minimal Cut Set (MCS), and determine the most dominant factor based on the Fussell-Vesely Importance Measure (IFV). Primary data were collected through a Likert scale 1–5 questionnaire distributed to expert respondents selected by purposive sampling, consisting of a Project Manager, Site Engineer, QC Engineer, supervisory consultant, and field supervisor directly involved in the project. The analysis was conducted using quantitative Fault Tree Analysis (FTA) comprising probability conversion, FTA diagram construction, MCS analysis, top event probability calculation, and IFV measurement. The results show that the highest probability values were obtained by X23 (bad weather) and X26 (community disturbance), each at P = 0.700. The Minimal Cut Set (MCS) analysis produced 21 MCS consisting of 12 first-order and 9 second-order MCS, with a top event probability of P(T) = 0.9996. The most dominant factor based on IFV was X23 (bad weather) with IFV = 0.7003, followed by X24 (government regulation changes) with IFV = 0.5502, indicating that external factors dominate the cost overrun risk on this project. These findings are expected to provide cost control recommendations for stakeholders in similar power plant projects in Indonesia.