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PENGENDALIAN DURASI PROYEK INFRASTRUKTUR MINYAK DAN GAS MENGGUNAKAN SINGULARITY FUNCTIONS-EARNED VALUE MANAGEMENT (SF-EVM)

*Daniel Steven Santoso  -  Universitas Pembangunan Nasional Veteran Jakarta, Indonesia
Alina Cynthia Dewi  -  Universitas Pembangunan Nasional Veteran Jakarta, Indonesia
Amenda Septiala Tarigan  -  Universitas Pembangunan Nasional Veteran Jakarta, Indonesia

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Abstract

Industri minyak dan gas bumi menghadapi tantangan kompleksitas tinggi yang kerap memicu deviasi jadwal. Metode Earned Value Management (EVM) konvensional memiliki keterbatasan akibat asumsi linearitas, sehingga kurang responsif terhadap dinamika tren kinerja. Penelitian ini membandingkan akurasi estimasi durasi proyek infrastruktur migas antara metode EVM dan Singularity Functions-Earned Value Management (SF-EVM). Validasi dilakukan menggunakan data historis hingga bulan ke-22 untuk memprediksi realisasi bulan ke-23 melalui metrik Absolute Percentage Error (APE). Selain itu, dilakukan analisis sensitivitas dengan memvariasikan nilai Earned Value (EV) dari 90% hingga 110% untuk menguji stabilitas model. Hasil penelitian menunjukkan metode EVM memberikan estimasi pesimis sebesar 58,14 bulan dengan tingkat kesalahan 4,34%. Sebaliknya, SF-EVM menghasilkan estimasi yang lebih realistis yakni 50,25 bulan dengan tingkat kesalahan yang lebih rendah, yaitu 3,84%. Analisis sensitivitas turut mengonfirmasi bahwa metode SF-EVM sangat stabil terhadap fluktuasi perubahan EV. Kesimpulannya, SF-EVM terbukti lebih andal sebagai instrumen pengendalian untuk menangkap diskontinuitas dan momentum pemulihan kinerja proyek secara presisi.

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Keywords: earned value management; infrastruktur minyak dan gas; pengendalian proyek; singularity functions

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  1. Alsugair, A. M., Al-Gahtani, K. S., Alsanabani, N. M., Hommadi, G. M., & Alawshan, M. I. (2024). An integrated DEMATEL and system dynamic model for project cost prediction. Heliyon, 10(4), e26166. https://doi.org/10.1016/j.heliyon.2024.e26166
  2. Chen, H. L., Chen, W. T., & Lin, Y. L. (2016). Earned value project management: Improving the predictive power of planned value. International Journal of Project Management, 34(1), 22–29. https://doi.org/10.1016/j.ijproman.2015.09.008
  3. Ezzeddine, A., & Fayek, A. R. (2022). Forecasting Construction Project Performance with Momentum Using Singularity Functions in LPS.Journal of Construction Engineering and Management, 148(8). https://doi.org/10.1061/(ASCE)CO.1943-7862.000232
  4. Handoko, A. E. (2024). Developing quality project schedule using GAO schedule assessment best practices in Indonesia’s national oil company. PM World Journal, 13(11), 1–21. https://pmworldlibrary.net/wp-content/uploads/2024/12/pmwj147-Dec2024-Handoko-project-schedule-using-GAO-best-pracices-in-Indonesias-national-oil-company.pdf
  5. Hermawan, D., Isvara, W., & Ichsan, M. (2024). Critical risk factors associated with schedule delays in gas processing facility projects: Case study in Indonesia. Global Business and Finance Review, 29(6),60–73. https://doi.org/10.17549/gbfr.2024.29.6.60
  6. Hussein, A. R. ., & Moradinia, S. F. (2024). Time and Cost Management in Water Resources Projects Utilizing the Earned Value Method. Journal of Studies in Science and Engineering, 4(1), 91–111. https://doi.org/10.53898/josse2024417
  7. Jamal, J., & Ian, M. R. (2025). Analisis faktor penyebab keterlambatan proyek konstruksi di Indonesia. Jurnal Kajian Teknik Sipil, 10(1), 1–8. https://doi.org/10.52447/jkts.v10i1.8071
  8. Kementerian Energi dan Sumber Daya Mineral. (2024, 16 Januari). PNBP migas sumbang Rp117 triliun ke kas negara. https://www.esdm.go.id/id/media-center/arsip-berita/pnbp-migas-sumbang-rp117-triliun-ke-kas-negara-
  9. Mamuye, Endale & Mengesha, Wubishet. (2024). Predicting construction cost under uncertainty using grey-fuzzy earned value analysis. Heliyon. 10. e27662. 10.1016/j.heliyon.2024.e27662. https://doi.org/10.1016/j.heliyon.2024.e27662
  10. Mayo-Alvarez, L., et al. (2022). A Systematic Review of Earned Value Management and Its Variants for Schedule Control in Projects. Sustainability, 14(22), 15259
  11. https://doi.org/10.3390/su142215259
  12. Mohammed, A., Bahatheq, A., Ghaithan, A., Alshibani, A., Mazher, K. M., & Alrashidi, A. (2025). Predicting schedule delays of construction projects in the oil and gas industry: A comparative study. Built Environment Project and Asset Management. Advance online publication
  13. https://doi.org/10.1108/BEPAM-12-2024-0286
  14. Ngo, K. A., Lucko, G., & Ballesteros-Pérez, P. (2022). Continuous earned value management with singularity functions for comprehensive project performance tracking and forecasting. Automation in Construction, 143, 104583
  15. Lu, S., & Pamadi, M. . (2023). Performance Analysis System Using Earned Value Method For Electrical Greenhouse Work Project In Batam City. Jurnal Indonesia Sosial Teknologi, 4(12), 2288–2296. https://doi.org/10.59141/jist.v4i12.828
  16. Semenova, T., & Churrana, N. (2025). Assessment of the projects’ prospects in the economic and technological development of the oil and gas complex in the Republic of Mozambique. Resources, 14(7), 106. https://doi.org/10.3390/resources14070106
  17. Zahoor, H., Khan, R. M., Nawaz, A., Ayaz, M., & Maqsoom, A. (2022). Project control and forecast assessment of building projects in Pakistan using earned value management. Engineering, Construction and Architectural Management, 29(2), 842-869

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