NAVIGATING THE LANDSCAPE OF INNOVATIVE TECHNOLOGIES IN CONSTRUCTION PROJECT MANAGEMENT: A COMPREHENSIVE REVIEW


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Dagou H. H., GÜRGÜN A. P., KOÇ K., Kunkcu H.

Proceedings on Engineering Sciences, vol.6, no.4, pp.1621-1632, 2024 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 4
  • Publication Date: 2024
  • Doi Number: 10.24874/pes06.04.021
  • Journal Name: Proceedings on Engineering Sciences
  • Journal Indexes: Scopus, Directory of Open Access Journals
  • Page Numbers: pp.1621-1632
  • Keywords: Artificial Intelligence (AI) in Construction, Building Information Modeling (BIM), Construction Project ManagementTechnology Integration, Emerging Technologies in Construction
  • Yıldız Technical University Affiliated: Yes

Abstract

This study was initiated with thorough investigation to determine the optimal Market Basket Analysis (MBA) algorithms for the Co-Market Intelligent Application using Association Rule Mining (ARM). An exploration evaluation was conducted to assess their suitability for integration into the Co-Market Intelligent application framework, focusing on three product categories: coconut non-food products, coconut food products, and sarakat products. Employing a model for Apriori with a minimum support of 0.2 and minimum confidence of 0.5 yielded remarkably high accuracies of 140% for coconut non-food and 72% for sarakat products while a model with minimum support of 0.2 and minimum confidence of 0.7 yielded 92% lift ratio for food products. For FP-Growth, a model with minimum support of 0.1 and minimum confidence of 0.5 demonstrated the best performance, achieving accuracies of 92% and 42% for coconut non-food and food products respectively. The findings of this study suggest that the selection of either the Apriori or FP-Growth algorithm, or a combination of both, tailored to the specific product categories, can significantly enhance the efficiency and accuracy of Market Basket Analysis in the Co-Market Intelligent Application, providing valuable insights for optimized decision-making and strategic planning in the targeted market sectors.