Generalized Additive Model Approach for Analyzing the Productivity of Irrigation Construction Workers

Authors

Tutang Muhtar Kamaludin Jurusan Teknik Sipil, Fakultas Teknik Universitas Taduako, Indonesia 94112
Bayu Rahmat Ramadhan Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Palu, Indonesia, 94112
Mastura Labombang Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Palu, Indonesia, 94112
Zet Mallisa Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Palu, Indonesia, 94112
Harun Mallisa Jurusan Teknik Sipil, Fakultas Teknik Universitas Tadulako, Palu, Indonesia, 94112
Moh Fikram Ladjatang Mahasiswa Jurusan Teknik Sipil, Fakultas Teknik Universitas Taduako, Indonesia 94112

DOI:

https://doi.org/10.22487/renstra.v7i1.827

Keywords:

pruductivity, model, workforce, projects, irrigation infrastructure

Abstract

Labor productivity is a critical determinant of success in infrastructure development projects. This study investigates the dominant factors influencing the productivity of irrigation construction workers by integrating Generalized Additive Models (GAM) and Monte Carlo simulation. Using data analyzed in R Statistics 4.3.0 for Windows, we employed GAM to identify nonlinear relationships between productivity and predictor variables, followed by a permutation-based Monte Carlo resampling approach (100 simulations) to validate critical predictors. Results reveal that wage policies, availability of safety equipment, and managerial practices are the most significant drivers of productivity. Methodologically, this research contributes a novel framework combining GAM’s flexibility with Monte Carlo’s robustness to quantify uncertainty, evaluated via the coefficient of determination (R²). The permutation-based variable importance analysis underscores the practical relevance of these factors, offering actionable insights for optimizing workforce management in irrigation infrastructure projects.

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References

L. Hai-Min, S. Wen-Juan, S. Shui-Long, and Z. An-Nan, “Risk Assessment Using a New Consulting Process in Fuzzy AHP”, Journal of Construction Engineering and Management, vol. 146, no. 3, pp. 1-16, 2020. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001757

T.G. Gezahegne and F.A. Robinson, “Hybrid GA-MANFIS Model for Organizational Competencies and Performance in Construction”, Journal of Construction Engineering and Management, vol. 148, no. 4, pp. 1-14, 2022. https://doi.org/10.1061/ (ASCE)CO.1943-7862.0002250

J. Tariq and S. Shujaa Safdar Gardezi, “Study the Delays and Conflicts for Construction Projects and Their Mutual Relationship: A Review,” Ain Shams Engineering Journal, vol. 14, no. 1, pp. 1-15, 2023. https://doi.org/10.1016/j.asej.2022.101815

A. Rathnayake and C. Middleton, “Systematic Review of the Literature on Construction Productivity”, Journal of Construction Engineering and Management, vol. 149, no. 6, pp. 1-12, 2023. https://doi.org/10.1061/JCEMD4.COENG-13045

B. Anif, “Construction Project Productivity in Indonesia,” American Research Journal of Business and Management, vol. 7, no. 1, pp. 1-9, 2021.

M.B. Shishehgarkhaneh, R.C. Moehler, Y. Fang, H. Aboutorab, and A.A. Hijazi, “Construction Supply Chain Risk Management”, Automation in Construction, vol. 162, pp. 1-14, 2024. https://doi.org/10.1016/j.autcon.2024.105396

P. Jalal and P. Shahsavand, Engineering Construction & Architectural Management, London: Project Management Institute, 2022.

D. Langford, M.R. Hancock, R.F. Fellows, and A.W. Gale, Human Resources Management in Construction, London: Routledge, 2014.

S. Mitoulis, S. Argyroudis, M. Panteli, C. Fuggini, S. Valkaniotis, and W. Hynes, “Conflict-Resilience Framework for Critical Infrastructure Peacebuilding”, Sustainable Cities and Society, vol. 91, pp. 1-18, 2023. https://doi.org/10.1016/j.scs.2023.104405

A.F. Elkliny, H.M. Sanad, and E.E. Etman, “Time-Cost-Quality Tradeoff Considering Resource-Scheduling Problems”, Ain Shams Engineering Journal, vol. 14, no. 11, pp. 1-14, 2023. https://doi.org/10.1016/j.asej.2023.102524

M. Salem, M. Asim, and R. Banerjee, “Identification of Success Factors in Construction Projects- A Systematic Literature Review”, International Journal for Research in Applied Science and Engineering Technology, vol. 10, no. 5, pp. 1437-1439, 2022. https://doi.org/10.22214/ijraset.2022.42526

S. Karn and K. Dahal, “Cost Optimization in Building Construction Projects with Special Reference to Kathmandu Valley of Nepal”, American Journal of Science, Engineering and Technology, vol. 6, no. 1, pp. 1-8, 2021. https://doi.org/10.11648/j.ajset.2021 0601.12

P. Tunji-Olayeni, A. Afolabi, R. Ojelabi, and B.A. Ayim, “Impact of Logistics Factors on Material Procurement for Construction Projects”, International Journal of Civil Engineering and Technology, vol. 8, pp. 1142-1148, 2017.

A. Gurmu and A. Aibinu, “Construction Equipment Management Practices for Improving Labor Productivity in Multistory Building Construction Projects”, Journal of Construction Engineering and Management, vol. 143, no. 10, pp. 1-18, 2017. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001384

F. Albtoush, D. Shu-Ing, A. Rahimi, A. Rahman, and A. Albtoush, “Factors Effecting the Cost Management in Construction Projects”, International Journal of Civil Engineering and Technology, vol. 11, no. 1, pp. 105-111, 2020.

J. Siddharth and J. Pitroda, “A Critical Literature Review on Factors Affacting in Selection of Construction Equipment”, International Journal of Advanced Technology in Engineering and Science, vol. 02, no. 12, pp. 559-567, 2014. https://www.doi.org/10.17577/IJERTV6IS020173

J. Hughes, Food and Agriculture, Roma: FAO, 2013.

Ministry of Public Works, Regulation on Construction Workforce Certification, Jakarta: BNSP, 2022.

OSHA, Safety and Competency in Construction Practices, New York: US. Department of Labor, 2022.

ILO, Upskilling Construction Workers: Non-Formal Training Strategies, Jenewa: International Labour Organization, 2023.

R. Wijaya and T. Sutrisno, “Bridging Indonesia’s Construction Skills Gap Through Vocational Training”, Engineering, Construction and Architectural Management”, vol. 28, no. 8, pp. 2105-2122, 2021.

U. Jacek, O.M. Tunde, W. Magdalena, and G. Marian, “Is Accreditation an Opportunity for Positive Change or a Mirage?”, Journal of Professional Issues in Engineering Education and Practice, vol. 140, no. 1, pp. 1-18, 2014. https://doi.org/10.1061/(ASCE) EI.1943-5541.0000172

World Bank, Procurement Standards for Infrastructure Development”, Washington: IBRD, 2023.

LPJK, Indonesian Construction Expert Certification Framework”, Jakarta: Lembaga Pengembangan Jasa Konstruksi, 2022.

Institute for Essential Services Reform, Indonesia Energy Transition Outlook, Jakarta: IESR, 2020.

FAO, Modern Irrigation Infrastructure Design Guidelines, Roma: Food and Agriculture Organization, 2020.

A.S. Gutterman, Organizational Performance and Effectiveness, New Jersey: John Wiley & Sons, 2023.

A. Rathnayake, D. Murguia, and C. Middleton, “Measuring Activity-Level Construction Productivity”, Journal of Construction Engineering and Management, vol. 150, pp. 1-18, 2024. https://doi.org/10.1061/JCEMD4.COENG-14602

OECD, Productivity Measurement Framework, Paris: Organisation for Economic Co-operation and Development, 2023.

PMI, Human Resource Factors in Construction Productivity, London: Project Management Institute, 2023.

Y. Zhang, “Determinants of Construction Productivity”, Journal of Construction Engineering, vol. 147, no. 8, pp. 1-14, 2021.

R-Studio Team, A Language and Environment for Statistical Computing, Boston: Massachusetts IT, 2021

R. Ihaka, “R: Past and Future History”, Proceedings of the 30th Symposium on the Interface, pp. 392-396, 1998.

R-Core Team, Writing R Extensions, Boston: Massachusetts IT, 2023.

C.P. Robert and G. Casella, The Metropolis—Hastings Algorithm BT - Monte Carlo Statistical Methods, New York: Springer, 2004

T.J. Hastie and R.J. Tibshirani, Generalized Additive Models, New Jersey: John Wiley & Sons, 2017.

L. Fahrmeir, Thomas Kneib, Stefan Lang, Brian D, and Marx, Regression, New York: McGraw-Hill, 2021.

G. James, D. Witten, T. Hastie, and R. Tibshirani, An Introduction to Statistical Learning, Berkeley: University of California, 2021.

J. Fox, Applied Regression Analysis And Generalized Linear Models, California: SAGE Publications, 2008.

J. Cohen, Statistical Power Analysis for the Behavioral Sciences, Lawrence Elbraum, New York: 1988.

M. Kuhn and K. Johnson, Applied Predictive Modeling, Singapore: Springer, 2023.

M. Wieling, “Analyzing Dynamic Phonetic Data Using Generalized Additive Mixed Modeling: A Tutorial Focusing on Articulatory Differences Between L1 and L2 Speakers of English”, Journal of Phonetics, vol. 70, pp. 86-116, 2018. https://doi.org/10.1016/j.wocn.2018.03.002

B. Georges, A. Michez, N. Latte, P. Lejeune, and Y. Brostaux, “Water Stream Heating Dynamics Around Extreme Temperature Events: An Innovative Method Combining GAM and Differential Equations”, Journal of Hydrology, vol. 601, pp. 1-15, 2021. https://doi.org/10.1016/j.jhydrol.2021. 126600

L. Breiman, “Random Forests,” Machine Learning, vol. 45, pp. 5-32, 2001. https://doi.org/10.1023/A:1010933404324

B.M. Greenwell and B.C. Boehmke, “Variable Importance Plots—An Introduction to the vip Package”, Research Journal, vol. 12, pp. 343-366, 2020.

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Published

2026-04-11

How to Cite

Kamaludin, T. M. ., Ramadhan, B. R. ., Labombang, M., Mallisa, Z. ., Mallisa, H. ., & Ladjatang, M. F. . (2026). Generalized Additive Model Approach for Analyzing the Productivity of Irrigation Construction Workers . REKONSTRUKSI TADULAKO: Civil Engineering Journal on Research and Development, 7(1), 77-86. https://doi.org/10.22487/renstra.v7i1.827