A Level 1 Cost Estimating Relationship Model for Airside Construction Cost Estimation of Greenfield Airports Without Intercept

  • Inayatullah Inayatullah Doctoral Program in Civil Engineering, Faculty of Engineering, Universitas Tarumanagara | Jakarta, Indonesia
  • Leksmono Suryo Putranto Doctoral Program in Civil Engineering, Faculty of Engineering, Universitas Tarumanagara | Jakarta, Indonesia
  • Tiopan H M Gultom Faculty of Engineering, Universitas Mulawarman| Jakarta, Indonesia
Keywords: cost estimating relationship, parametric cost model, greenfield airport, earthwork, construction cost estimation

Abstract

Cost estimation for greenfield airports in archipelagic countries such as Indonesia faces a distinctive problem: comparable projects are too few for multiple linear regression to be validly applied. This study develops and tests a Level 1 Cost Estimating Relationship (CER) in factor form without an intercept for the airside pavement components of greenfield airports. The model dissects unit cost into three core components, namely runway (including turning area), taxiway, and apron area, drawn from the budget documents of four benchmark greenfield airports. All costs are equalized to a Jakarta 2025 basis through double normalization of time and region, together with a standard scope rule that unifies the content of every budget item. Coefficients are calibrated with the Minimum Unbiased Percentage Error (MUPE) method, re-verified with the Zero-bias Minimum Percent Error (ZMPE) method, and validated through Leave-One-Out (LOO) cross-validation. The most important finding is that earthwork accounts for an average of 73.7% of airside cost across the four benchmark airports and is governed by site class rather than pavement area. The resulting model is Y = (1.1001 X1 + 0.9227 X2 + 1.2825 X3) x M(s) x (IKKp / 113.17) x (IHPBp / 101.39), where LOO validation on the core-pavement-and-ancillary cost yields a prediction error of 34.9% and a bias of +10.5%, equivalent to AACE Class 4-5 accuracy. According to ISPA, GAO, and NASA guidance this accuracy is acceptable for master-planning-stage estimates and is categorized as marginal to good.

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Published
2026-09-30