Model Probabilistik Penentuan Bobot Biaya Tenaga Kerja, Material, dan Peralatan pada Proyek Gedung Menggunakan Simulasi Monte Carlo
Abstract
Keywords
Full Text:
PDFReferences
Abdel-hafeez, M. M., Attar, S. S. E.-, & Abdel-hafez, W. A. (2016). Faculty of Engineering - Port Said University Risk Management as an Approach to Control Construction Projects Costs. 1.
Afzal, F., Shao, Y., Junaid, D., & Hanif, M. S. (2020). Cost-Risk Contingency Framework for Managing Cost Overrun in Metropolitan Projects: Using Fuzzy-Ahp and Simulation. International Journal of Managing Projects in Business, 13(5), 1121–1139. https://doi.org/10.1108/ijmpb-07-2019-0175
Al-Emad, N., Abdul Rahman, I., Nagapan, S., & Gamil, Y. (2017). Ranking of Delay Factors for Makkah’s Construction Industry. MATEC Web of Conferences, 103, 0–7. https://doi.org/10.1051/matecconf/201710303001
Ashtari, M. A., Ansari, R., Hassannayebi, E., & Jeong, J. (2022). Cost Overrun Risk Assessment and Prediction in Construction Projects: A Bayesian Network Classifier Approach. Buildings, 12(10), 1660. https://doi.org/10.3390/buildings12101660
Ate, B., & Eirgash, M. A. (2025). Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects. Buildings, 2025(15), 1–16. https://doi.org/https:// doi.org/10.3390/buildings15142388
Belay, S. M., Tilahun, S., Yehualaw, M., Matos, J., Sousa, H., & Workneh, E. T. (2021). Analysis of Cost Overrun and Schedule Delays of Infrastructure Projects in Low Income Economies : Case Studies in Ethiopia. Advances in Civil Engineering, 2021(2021), 15. https://doi.org/10.1155/2021/4991204
Bouayed, Z. (2016). Using Monte Carlo Simulation To Mitigate The Risk Of Project Cost Overruns. J. of Safety and Security Eng, 6(2), 293–300. https://doi.org/10.2495/SAFE-V6-N2-293-300
Budiharsanto, H. N., & Mardiaman. (2026). Evaluasi Wastage Level Material Struktur (Besi, Kayu, dan Beton) pada Proyek Rumah Susun Pemerintah di Surakarta. Jurnal Talenta Sipil Vol, 9(1), 545–551. https://doi.org/10.33087/talentasipil.v9i1.1266
Caron, F., Ruggeri, F., & Merli, A. (2013). A Bayesian Approach to Improve. Project Management Journal, 44(1), 3–16. https://doi.org/10.1002/pmj
Daundkar, S. T., Thakur, M. S., & Awad, M. S. (2022). Analysis of Construction Project Cost Overrun by Statistical Method. International Journal for Research in Applied Science and Engineering Technology, 10(5), 5200–5207. https://doi.org/10.22214/ijraset.2022.43660
Habibi, M., & Kermanshachi, S. (2018). Phase-Based Analysis of Key Cost and Schedule Performance Causes and Preventive Strategies. Engineering Construction & Architectural Management, 25(8), 1009–1033. https://doi.org/10.1108/ecam-10-2017-0219
Hannan, A., Ahmed, A., Ashraf, T., & Bai, Q. (2017). Estimation of Highway Project Cost Using Probabilistic Technique. Destech Transactions on Engineering and Technology Research, ictim. https://doi.org/10.12783/dtetr/ictim2016/5523
Ikechukwu, A. C., Fidelis, I. E., & Kelvin, O. A. (2017). Causes and Effects of Cost Overruns in Public Building Construction. IOSR Journal of Business and Management (IOSR-JBM), 19(7), 13–20. https://doi.org/10.9790/487X-1907021320
Islam, M. S., Mohandes, S. R., Mahdiyar, A., Fallahpour, A., & Olanipekun, A. O. (2022). A Coupled Genetic Programming Monte Carlo Simulation–Based Model for Cost Overrun Prediction of Thermal Power Plant Projects. Journal of Construction Engineering and Management, 148(8). https://doi.org/10.1061/(asce)co.1943-7862.0002327
Kim, B., & Pinto, J. K. (2019). What CPI = 0.85 Really Means: A Probabilistic Extension of the Estimate at Completion. Journal of Management in Engineering, 35(2). https://doi.org/10.1061/(asce)me.1943-5479.0000671
Lorenzo, D. C., Poza, D., Villafáñez, F., & Acebes, F. (2024). Cost Contingency Estimation: A New Method for Quantitative Risk Analysis Applied to a Real Construction Project. Dyna Ingenieria E Industria, 99(1), 106–112. https://doi.org/10.6036/10815
Luong, K. S., & Doan, N. S. (2025). Probabilistic Forecasting of Project Cost and Schedule Using Earned Value Management and Monte Carlo Simulation. International Journal of Marine Science and Technology, 1(1), 1–7. https://doi.org/https://doi.org/10.65154/ijmst.21
Naeini, M. E. (2013). Cost control development under stochastic performance control 3 . Approaches to Measure Project Per-. International Journal of Economics, Finance and Management Sciences, 1(1), 54–60. https://doi.org/10.11648/j.ijefm.20130101.17
Niazi, G. A., & Painting, N. (2017). Significant Factors Causing Cost Overruns in the Construction Industry in Afghanistan. Procedia Engineering, 182, 510–517. https://doi.org/10.1016/j.proeng.2017.03.145
Putu, N., Sugiandhari, G., Respati, R., Studi, P., Sipil, T., Palangkaraya, U. M., Tengah, K., Studi, P., Sipil, T., Palangkaraya, U. M., Tengah, K., Studi, P., Sipil, T., Palangkaraya, U. M., & Tengah, K. (2024). Implementasi Value Engineering Untuk Optimasi Pembiayaan Pada Proyek Konstruksi. JMTS: Jurnal Mitra Teknik Sipil, 7(2), 465–478.
Rivky, R. (2024). Value Engineering Building Structure Work Asn Paspampres Pupr Precast With Lead Rubber Bearing. Injuruty: Interdiciplinary Journal and Humanity, 3(2), 196–212.
Sadeghi, N., Fayek, A. R., & Pedrycz, W. (2010). Fuzzy Monte Carlo Simulation and Risk Assessment in Construction. Computer-Aided Civil and Infrastructure Engineering, 25(4), 238–252. https://doi.org/10.1111/j.1467-8667.2009.00632.x
Saraswati, N., & Wiguna, I. P. A. (2024). Contractor’s Perspective on Execution Method Impact to Cost Overrun in Bali’s Building Construction. Jurnal Ilmiah Teknik Sipil, 28(1), 10–17. https://doi.org/10.24843/jits.2024.v28.i01.p02
Triatmojo, D., Adi, H. P., & Poedjiastoeti, H. (2025). Risk Factor Analysis on Contingency Costs of Phase I Wastewater Network Project in Bogor City. Indonesian Journal of Social Technology, 6(2), 882–897. https://doi.org/10.59141/jist.v6i2.8856
Xie, W., Deng, B., Yin, Y., Lv, X., & Deng, Z. (2022). Critical Factors Influencing Cost Overrun in Construction Projects : A Fuzzy Synthetic Evaluation. Buildings, 12(2028), 1–19.
Zhao, M., & Zi, X. (2021). Using Earned Value Management with exponential smoothing technique to forecast project cost Using Earned Value Management with exponential smoothing technique to forecast project cost. https://doi.org/10.1088/1742-6596/1955/1/012101
DOI: http://dx.doi.org/10.33087/talentasipil.v9i2.1333
Refbacks
- There are currently no refbacks.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Jurnal Talenta Sipil, Faculty of Engineering, Batanghari University |


