Application Of Analytic Hierarchy Process AHP Method In Material Selection For Construction

Authors

  • Warkianto Widjaja Universitas Kebangsaan Republik Indonesia Author
  • Jonggi Harianja Pensiunan Kementerian PUPR Author
  • Edison Hatoguan Manurung Universitas MPU Tantular Jakarta Author
  • Suharyanto Suharyanto Teknik Industri, Universitas Kebangsaan Republik Indonesia Author

DOI:

https://doi.org/10.62872/v0qvdx61

Keywords:

Analytic Hierarchy Process (AHP), construction materials, structural steel, data-driven decisions, sustainability

Abstract

Material selection in the construction industry is a strategic decision that affects the cost efficiency, durability, and sustainability of a project. This study applies the Analytic Hierarchy Process (AHP) method to determine the best construction material based on four main criteria: mechanical strength, environmental resistance, cost efficiency, and environmental sustainability. The hierarchical structure is built with three levels: material selection objectives, evaluation criteria, and compared material alternatives—namely structural steel, cross-laminated timber (CLT), and reinforced concrete. The assessment uses the Saaty scale (1–9), then the matrix is normalized to obtain priority weights. Consistency tests are carried out by calculating the maximum eigenvalue (λmax), Consistency Index (CI), and Consistency Ratio (CR). The results show that structural steel has the highest weight (0.4888093), making it the best choice compared to CLT and reinforced concrete. This study confirms that the AHP method is able to reduce subjectivity in decision making with a data-driven approach. Integration with technologies such as Building Information Modeling (BIM) and Artificial Intelligence (AI) can improve the accuracy of the analysis. Thus, this method can be a solution in selecting construction materials that are more systematic and sustainable.

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Published

2025-02-28

How to Cite

Application Of Analytic Hierarchy Process AHP Method In Material Selection For Construction. (2025). Journal of Renewable Engineering, 2(1), 20-26. https://doi.org/10.62872/v0qvdx61