Article Per Year (5 Year)
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This Author published in this journals
All Journal International Journal of Cyber and IT Service Management (IJCITSM) International Transactions on Artificial Intelligence (ITALIC)
Ridhuan Ahsanitaqwim
University of Raharja
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science

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AI-Based Strategies to Improve Resource Efficiency in Urban Infrastructure Ninda Lutfiani; Nuke Puji Lestari Santoso; Ridhuan Ahsanitaqwim; Untung Rahardja; Achani Rahmania Az Zahra
International Transactions on Artificial Intelligence Vol. 2 No. 2 (2024): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v2i2.545

Abstract

Rapid urbanization has significantly increased urban populations, leading to higher consumption of resources such as energy, water, and fuel. Resource efficiency is crucial to managing urban growth in an environmentally friendly and economical manner. This research aims to explore the role of artificial intelligence (AI) in improving resource efficiency in urban infrastructure. By leveraging AI technology, this study seeks to find innovative solutions that can optimize resource use, enhance energy management, and improve monitoring and control of infrastructure systems. The findings indicate that the implementation of AI can increase energy efficiency by 15%, reduce transportation travel times by 15%, and improve water management efficiency by 15%. These results demonstrate that AI can be an effective tool in supporting the sustainability of urban infrastructure, reducing operational costs, and mitigating environmental impacts. This research provides practical guidance for city managers and policymakers in designing and implementing smarter and more efficient technological solutions.
Artificial Intelligence in Autonomous Vehicles: Current Innovations and Future Trends Nuraini Diah Noviati; Fengki Eka Putra; Sadan Sadan; Ridhuan Ahsanitaqwim; Nanda Septiani; Nuke Puji Lestari Santoso
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 4 No. 2 (2024): October
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v4i2.161

Abstract

Artificial Intelligence (AI) has become a cornerstone in advancing autonomous vehicles, enabling realtime decision making, object detection, and automation in driving systems. This study aims to explore key AI innovations, including Machine Learning (ML) algorithms, computer vision, and reinforcement learning, that contribute to the development of autonomous vehicles. A qualitative approach} was adopted to analyze both current applications and future innovations of AI in autonomous vehicles. The study highlights various current AI applications in autonomous vehicles, such as automated safety features, advanced navigation systems, and adaptive cruise control. These technologies demonstrate how AI enhances vehicle functionality and improves safety in today driving environment. Looking ahead, AI is expected to enable full autonomy in vehicles, foster integration with smart city infrastructures, and drive innovations in fleet management. These advancements are anticipated to significantly improve vehicle safety, operational efficiency, and the overall user experience, solidifying AI as the fundamental technology for the future of intelligent transportation systems.
Co-Authors Achani Rahmania Az Zahra Fengki Eka Putra Nanda Septiani Ninda Lutfiani Nuke Puji Lestari Santoso Nuke Puji Lestari Santoso Nuraini Diah Noviati Sadan Sadan Untung Rahardja