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Journal of ICT, Design, Engineering and Technological Science
Published by Universitas Muhammadiyah Purwokerto
ISSN : -     EISSN : 26042673     DOI : https://doi.org/10.33150/JITDETS-8.1.1
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Mechanical Engineering
Journal of ICT, Design, Engineering and Technological Science (JITDETS) focuses on the logical ramifications of advances in information and communications technology. It is expected for all sorts of experts, be it scientists, academicians, industry, government or strategy producers. It, along these lines, gives an exceptional discussion to papers covering application-based research subjects significant to assembling procedures, machines, and process reconciliation. JITDETS maintains the high standard of excellence of publishing. This is guaranteed by subjecting each paper to a strict evaluation strategy by individuals from the universal publication counseling board. The goal is solid to set up that papers submitted do meet all the requirements, particularly with regards to demonstrated application-based research work. It is not satisfactory that papers have a hypothetical substance alone; papers must exhibit producing applications.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 82 Documents
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Technology Readiness and Safety Outcomes in Construction: The Mediating Role of Worker Competence and Moderating Role of Top Management Support Ishtiaq Ahmad
Journal of ICT, Design, Engineering and Technological Science Volume 9, Issue 2
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS‑9.2.6

Abstract

Construction projects remain highly vulnerable to accidents due to dynamic workflows, hazardous environments, and limitations of conventional safety management approaches. With the growing adoption of Industry 4.0 technologies, construction organizations are in‑creasingly investing in digital safety tools; however, their effectiveness depends on organizational readiness and workforce capability to im‑plement them. Grounded in Socio‑Technical Systems (STS) Theory, this study examines the impact of Technology Readiness (TR) on Safety Climate (SC) and Safety Performance (SP), while assessing the mediating role of Worker Competence (WC)and the moderating influence of Top Management Support (TMS). A quantitative cross‑sectional survey was conducted using responses from 420 construction professionals drawn from both public (n=200) and private (n=220) sector organizations. An engineering‑oriented predictive modeling approach was applied, and the model demonstrated strong predictive performance, explaining 62% of the variance in safety climate (R²=0.62) and 58% in safety perfor‑mance (R²=0.58) with acceptable prediction error (SC: RMSE=0.41, MAE=0.32; SP: RMSE=0.45, MAE=0.35). Scenario analysis indicated that high technology readiness substantially improves predicted SC and SP, while competence improvement and strong management support generate similarly large gains in safety outcomes. Sensitivity analysis identified worker competence as the most influential predictor for both SC and SP,followed by technology readiness and top management support. Further, the sector‑wise comparison revealed that private sector organizations demonstrated a stronger link between technology readiness and increases in worker competence, as well as greater improvements in safety out‑comes associated with readiness, compared to public sector organizations. This suggests that private sector organizations were more effective at converting digital investments into competence and safety gains, possibly due to fewer institutional barriers or different organizational struc‑tures. The study concludes that sustainable safety improvement requires integrated strategies that enhance technology readiness, strengthen workforce competence, and reinforce leadership support to maximize the operational safety value of digital transformation in construction or‑ganizations.
A Custom CNN Architecture for Image Recognition using CIFAR‑10 Hayden Bin Nor Azman; Abdul Salam Shah
Journal of ICT, Design, Engineering and Technological Science Volume 8, Issue 2
Publisher : Journal of ICT, Design, Engineering and Technological Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33150/JITDETS-8.2.6

Abstract

Deep Learning algorithms have remained prominent in image classification across various domains. CNNs have modernized the process, enabling automated classification in new fields. Traditional models suffer from lower accuracy largely due to manual feature extraction. To address challenges in modern algorithms, this paper proposes a CNN‑based model for the multi‑class problem using the CIFAR‑10 dataset. The hyperparameters have been carefully selected to achieve higher accuracy while avoiding overfitting. Data augmentation and dropout layers contributed to achieving 85.49% accuracy

Page 9 of 9 | Total Record : 82

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