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All Journal Rekayasa Sipil Jurnal Teknik Sipil dan Perencanaan
Nugroho , Guntur
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Civil Engineering, Building, Construction & Architecture

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Evaluating the Performance of Python-Based Machine Learning in Earthquake-Resistant Building Design: Fuqaha, Sameh; Nugroho , Guntur
Rekayasa Sipil Vol. 19 No. 2 (2025): Rekayasa Sipil Vol. 19 No. 2
Publisher : Department of Civil Engineering, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.rekayasasipil.2025.019.02.9

Abstract

This study investigates the feasibility of applying artificial intelligence (AI)-based machine learning techniques, specifically a Multiple Linear Regression (MLR) model implemented in Python, for earthquake-resistant building design. The AI-based predictions are compared against conventional SAP2000 structural analysis. As one of the most seismically active regions globally, Indonesia urgently requires efficient and accurate seismic design methodologies. Traditional approaches, while reliable, are often time-consuming and labor-intensive, whereas AI offers rapid data processing and automation. This research predicted key structural parameters—including mass participation ratio, base shear force, inter-story drift, and structural period—using the MLR model and benchmarked against SAP2000 simulations. The AI-based predictions exhibited excellent alignment, with an average deviation of only 0.016%. Statistical validation showed an R² score of 0.999 and a p-value of 0.738, confirming no significant difference between the two methods. Moreover, the AI model significantly reduced computational time, completing analyses within seconds compared to the extended duration required by SAP2000. Despite these advantages, the current AI framework lacks a 3D modeling interface, limiting its applicability for detailed structural design. Future research should enhance AI capabilities by integrating parametric modeling tools and Building Information Modeling (BIM) platforms to support broader implementation in earthquake-resistant structural engineering.
Seismic Stiffness Evaluation of RC Dual Systems in Varying Geometries: A Pushover-Based Study Using Indonesian Codes Fuqaha, Sameh; Nugroho , Guntur
Jurnal Teknik Sipil dan Perencanaan Vol. 27 No. 2 (2025): Jurnal Teknik Sipil dan Perencanaan
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jtsp.v27i2.25494

Abstract

This study evaluates the seismic performance of reinforced concrete (RC) dual systems that combine moment-resisting frames with shear walls, using nonlinear pushover analysis in accordance with Indonesian seismic design codes (SNI 1726:2019 and SNI 2847:2019). A total of 32 analytical models were developed to examine the influence of four critical parameters: story height (3–10 stories), span length (5.5–6.5 m), shear wall thickness (200–250 mm), and concrete compressive strength (20–25 MPa). The elastic stiffness factor was determined as the base shear ratio to roof displacement at the onset of first hinge formation. In contrast, base shear capacity was derived from the pushover curves. Results show that geometric parameters exert the most decisive influence on seismic response, with stiffness decreasing by more than 50 percent as story height increases and by approximately 8 percent with longer spans. Material enhancements provide only modest gains of 2 to 7 percent. These findings emphasize the dominant role of structural configuration in drift control and ductility demand, offering practical recommendations for optimizing RC dual systems under Indonesian codes and improving the resilience of mid- to high-rise buildings in seismic regions.
Co-Authors Fuqaha, Sameh