Analysis of Project Performance and the Selection of Mitigation Strategies for Fiscal Disruptions Due to Government Budget Relaxation Policies
Downloads
Changes in budget allocation mechanisms and delays in fund disbursement have adversely affected project schedules, cost efficiency, and cash flow stability. This study aims to quantitatively evaluate the impact of fiscal disruption on project performance using Earned Value Management (EVM) indicators—namely the Schedule Performance Index (SPI) and Cost Performance Index (CPI)—and to identify the most feasible managerial mitigation strategy under constrained fiscal conditions. The research adopts a quantitative-dominant mixed-methods approach utilizing secondary data derived from official project documents, including S-curves, progress reports, cash flow statements, and government fiscal policy regulations. Project performance is assessed through EVM, while financial conditions are evaluated using Net Cash Flow (NCF) and Net Profit (NP) analysis. Several alternative funding strategies are analyzed using Discounted Cash Flow (DCF) techniques such as Net Present Value (NPV), Internal Rate of Return (IRR), Discounted Payback Period (DPP), and Debt Service Coverage Ratio (DSCR). The alternatives are subsequently ranked using a Multi-Criteria Decision Making (MCDM) approach based on a Weighted Scoring Model (WSM). The results indicate that fiscal adjustment policies significantly deteriorated project performance, as reflected by an SPI of 0.669 and a CPI of 0.957 as of June 2025. Among the evaluated mitigation strategies—internal funding, external funding, partial PPP, and a combination of internal–external funding—the combined strategy yields the most balanced technical and financial performance. Although it does not generate the highest profit, this strategy demonstrates superior overall feasibility and resilience under fiscal pressure.
Abdel-Basset, M., Ding, W., Mohamed, R., & Metawa, N. (2020). An integrated plithogenic MCDM approach for financial performance evaluation of manufacturing industries. Risk Management, 22(3), 192–218.
Ahinsah-Wobil, I. (2024). The impact of public financial management regulations on project continuity in Ghana. Available at SSRN 4796109.
Batselier, J., & Vanhoucke, M. (2015). Empirical evaluation of earned value management forecasting accuracy for time and cost. Journal of Construction Engineering and Management, 141(11). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001008
Brigham, E. F., & Houston, J. F. (2019). Fundamentals of financial management (15th ed.). Cengage Learning.
David, A., Devito, A. C., & Gottfried, A. (2016). Public private partnerships from the point of view of large construction companies. Proceedings of International Structural Engineering and Construction. https://doi.org/10.14455/ISEC.RES.2016.66
Fahira Rhomianti Putri, Susanti, B., & Toyfur, M. F. (2023). Identifikasi risiko kritis yang memengaruhi aspek finansial proyek KPBU jalan tol. Jurnal Teknik Sipil Universitas Syah Kuala, 20(1). https://jurnal.usk.ac.id/JTS/article/view/30332
Fleming, Q. W., & Koppelman, J. M. (2020). Earned value project management (5th ed.). Project Management Institute.
Ghalib, H., El-Khorazaty, M. T., & Serag, Y. (2021). New capital cities as tools of development and nation-building: Review of Astana and Egypt’s new administrative capital city. Ain Shams Engineering Journal, 12(3), 3405–3409. https://doi.org/10.1016/j.asej.2020.11.014
Harake, M. F. (2025). Navigating economic crises: Strategic project management for agility, resilience, and innovation. PM World Journal, 14.
Hartono, H. (2025). Urgensi Instruksi Presiden Nomor 01 Tahun 2025 terhadap pelaksanaan APBN di Kementerian/Lembaga Tahun 2025. Indonesian Research Journal on Education, 5(1), 2666–2672. https://doi.org/10.31004/irje.v5i2.2327
Instruksi Presiden Republik Indonesia Nomor 1 Tahun 2025. (2025).
Jato-Espino, D., Castillo-López, E., Rodríguez-Hernández, J., & Canteras-Jordana, J. C. (2014). A review of application of multi-criteria decision-making methods in construction. Automation in Construction, 45, 151–162. https://doi.org/10.1016/j.autcon.2014.05.013
Kasmir. (2016). Analisis laporan keuangan. PT RajaGrafindo Persada.
Khanh, H. D. (2026). Evaluating internal risks of slow disbursement in Vietnam’s state-funded construction projects: A fuzzy multi-criteria approach. Journal of Financial Management of Property and Construction, 1–26.
Project Management Institute. (2017). A guide to the project management body of knowledge (6th ed.). Project Management Institute.
Saputra, R. A., Yuwono, B. E., & Kawanda, A. (2021). The effect of financing delays on soil improvement projects: A case study of combining vertical drain with preloading. AIP Conference Proceedings, 2441(1), 040002. https://doi.org/10.1063/5.0073549
Shimamura, T., & Mizunoya, T. (2020). Sustainability prediction model for capital city relocation in Indonesia based on inclusive wealth and system dynamics. Sustainability, 12(10). https://doi.org/10.3390/su12104336
Yescombe, E. R., & Farquharson, E. (2018). Public-private partnerships for infrastructure: Principles of policy and finance (2nd ed.). Butterworth-Heinemann. https://www.sciencedirect.com/book/9780081007662/public-private-partnerships-for-infrastructure
Yu, X., Wu, X., & Huo, T. (2020). Combine MCDM methods and PSO to evaluate economic benefits of high-tech zones in China. Sustainability, 12(18), 7833.
Zhao, H., Zhao, H., & Guo, S. (2018). Comprehensive performance evaluation of electricity grid corporations employing a novel MCDM model. Sustainability, 10(7), 2130.
Copyright (c) 2026 Aristo Yonghy Robertus, Bambang Endro Yuwono
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
