Physical progress analysis of structure works using earned value management integrated with artificial neural network

Muhammad Farhan; Apif Miptahul Hajji; Aisyah Larasati

doi:10.1063/5.0072586

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Physical progress analysis of structure works using earned value management integrated with artificial neural network

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Muhammad Farhan, Apif Miptahul Hajji, Aisyah Larasati

2021 AIP Conference Proceedings Vol. 2447 Conference paper Cited by 0 SDG 9SDG 16

Abstract

Analysis of physical progress is useful for knowing project conditions and avoiding potential delays in construction projects. Analysis in this study aims to evaluate physical progress and estimate the completion time of structure works of Integrated Building Classroom State University of Malang (GKB UM) by integrating Earned Value Management and Artificial Neural Network. The results showed that the cumulative physical progress of the structural work was delayed by 24 weeks. The delay in loading test bored pile due to weather, damage to the tower crane and concrete pump tools, mobilization of tools and design changes to the superstructure were some of the problems encountered during the process of building structure works on GKB UM. The Artificial Neural Network model produces a small deviation between the predicted and the actual physical progress and suitable for estimating project completion. © 2021 Author(s).

Affiliations

Industrial Engineering Study Program, State University of Malang, Indonesia; Civil Engineering Study Program, State University of Malang, Indonesia

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