Pemodelan Estimasi Biaya Kontingensi Pada Proyek Konstruksi Jalan Raya Berbasis Metode Analisis Risiko

Andy Sutikno, Mohammad Arif Rohman

Abstract


Ketidakpastian risiko pada proyek konstruksi jalan raya mendorong perkiraan biaya kontingensi di estimasi secara tradisional berdasarkan penilaian subyektif seperti 5-10% dari biaya yang diperkirakan dengan mempertimbangkan proyek sejenis yang pernah dikerjakan. Metode tersebut secara ilmiah tidak bisa diterima dan sulit untuk dipertahankan keakurasiannya. Studi ini mengusulkan metode pengembangan model biaya kontingensi dari perspektif pemilik proyek yang dapat mengakomodasi penilaian subjektif berdasarkan risiko. Identifikasi variabel risiko diperoleh dari survei pendahuluan, wawancara, penyebaran kuesioner dan studi literatur, sedangkan perhitungan pemodelan biaya kontingensi menggunakan simulasi Monte Carlo. Hasil penelitian menunjukkan bahwa perkiraan biaya kontingensi rata-rata adalah 8,92% dari rencana anggaran proyek. Tingkat kesalahan pengujian model adalah 0,21% dari batas kesalahan yang diijinkan dan hasil validasi menunjukkan bahwa nilai analisis prediktif berada dalam akurasi 20% dibandingkan dengan biaya kontingensi yang sebenarnya.

Keywords


Risiko royek, Simulasi Monte Carlo, Biaya kontingensi

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References


S. Akintoye and M. J. MacLeod, “Risk analysis and management in construction,” International Journal of Project Management, vol. 15, no. 1, pp. 31–38, 1997, doi: 10.1016/S0263-7863(96)00035-X.

S. Mak, J. Wong, and D. Picken, “The effect on contingency allowances of using risk analysis in capital cost estimating: A Hong Kong case study,” Construction Management and Economics, vol. 16, no. 6, pp. 615–619, 1998, doi: 10.1080/014461998371917.

D. Baccarini, “Estimating Project Cost Contingency - A Model and Exploration of Researc,” 20th Annual ARCOM Conference, vol. 1, no. September, pp. 105–13, 2004.

A. Idrus, M. Fadhil Nuruddin, and M. A. Rohman, “Development of project cost contingency estimation model using risk analysis and fuzzy expert system,” Expert Systems with Applications, vol. 38, no. 3, pp. 1501–1508, 2011, doi: 10.1016/j.eswa.2010.07.061.

J. F. Al-Bahar and K. C. Crandall, “Systematic risk management approach for construction projects By Jamal F. Al-Bahar 1 and Keith C. Crandall, 2 Member, ASCE,” Engineering, vol. 116, no. 3, pp. 533–546, 1991.

K. W. Chau, “The validity of the triangular distribution assumption in Monte Carlo simulation of construction costs: Empirical evidence from Hong Kong,” Construction Management and Economics, vol. 13, no. 1, pp. 15–21, 1995, doi: 10.1080/01446199500000003.

P. Bakhshi and A. Touran, “An overview of budget contingency calculation methods in construction industry,” Procedia Engineering, vol. 85, pp. 52–60, 2014, doi: 10.1016/j.proeng.2014.10.528.

J. I. Ortiz-González, E. Pellicer, and G. Howell, “Contingency management in construction projects: A survey of spanish contractors,” 22nd Annual Conference of the International Group for Lean Construction: Understanding and Improving Project Based Production, IGLC 2014, pp. 195–206, 2014.

S.-H. Jan and S. P. Ho, “Construction Project Buffer Management in Scheduling Planning and Control,” Proceedings of the 23rd International Symposium on Automation and Robotics in Construction, no. October 2006, 2017, doi: 10.22260/isarc2006/0158.

L. Para-González, C. Mascaraque-Ramírez, and A. E. Madrid, “Obtaining the budget contingency reserve through the monte carlo method: Study of a ferry construction project,” Brodogradnja, vol. 69, no. 3, pp. 79–95, 2018, doi: 10.21278/brod69305.

R. E. Adaurhere, I. Musonda, and C. S. Okoro, “Construction contingency determination: A review of processes and techniques,” International Conference on Construction in the 21st Century, pp. 1–11, 2019.

S. Theodoridis and S. Theodoridis, “Chapter 14 – Monte Carlo Methods,” Machine Learning, pp. 707–744, 2015.

B. A. Traynor and M. Mahmoodian, “Time and cost contingency management using Monte Carlo simulation,” Australian Journal of Civil Engineering, vol. 17, no. 1, pp. 11–18, 2019, doi: 10.1080/14488353.2019.1606499.

S.Poulter, “Monte Carlo Simulation in Environmental Risk Assessment--Science, Policy and Legal Issues,” RISK: Health, Safety & Environment (1990-2002), vol. 9, no. 1, p. 4, 1998.




DOI: http://dx.doi.org/10.12962/j2579-891X.v20i3.14100

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