Improving Improving Efficiency and Accuracy of Quantity Take-Off Through BIM Integration: A Case Study of the D Lecture Hall Building at Malikussaleh University

Abstract

Abstract. Quantity Take-Off (QTO) calculation is a crucial step in construction planning to determine material needs with high accuracy. However, traditional methods such as manual calculations often fail to meet accuracy demands, especially in projects with complex designs. This study compares manual methods, Revit, and Clash Detection in generating QTO for the D Lecture Hall building project at Malikussaleh University. The aim of this research is to analyze the quantitative differences between methods and assess which method is the most effective. The research method involves calculating the QTO for structural and architectural elements using the three methods, followed by an analysis of the average differences in results. The findings show that the manual method has an average difference of 35.76% for structural elements and 43.14% for architectural elements when compared to Revit. The difference between manual and Clash Detection is slightly smaller, with 33.09% for structural elements and 42.41% for architectural elements. Conversely, the difference between Revit and Clash Detection is very small, only 1.51% for structural elements and 3.98% for architectural elements. While the QTO results between Revit and Clash Detection are almost identical, Clash Detection offers the additional advantage of validation, ensuring that the design is free from clashes between elements. This study concludes that Clash Detection is the most effective method in generating QTO because it not only provides accurate results but also ensures that the design is ready for implementation without technical errors. By integrating BIM technology, this research offers a more efficient and accurate approach to QTO calculation, serving as a guideline for construction project managers in handling complex designs more effectively.   Keywords: Quantity Take-Off (QTO), Clash Detection, Building Information Modeling (BIM).