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International Journal of Technology and Modeling
Published by Etunas Sukses Sistem
ISSN : -     EISSN : 29646847     DOI : https://doi.org/10.63876/ijtm
Core Subject : Science, Education, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics
International Journal of Technology and Modeling (e-ISSN: 2964-6847) is a peer-reviewed journal as a publication media for research results that support research and development of technology and modeling published by Etunas Sukses Sistem. International Journal of Technology and Modeling is published every four months (April, August, December). This journal is expected to be a vehicle for publishing research results from practitioners, academics, authorities, and related communities. IJTM aims to publish high-quality, original research, theoretical studies, and practical applications while promoting a global perspective on technology and modeling. The journal is dedicated to providing a forum for knowledge exchange and fostering cross-disciplinary collaboration, ensuring that research published within its pages contributes to the advancement of science and technology worldwide.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2023)" : 5 Documents clear
Simulating the Movement of Planets in the Solar System Using a Linear System Nurul Fadhilah; Muarief, Muchammad; Aningtias, Rizka Fitri
International Journal of Technology and Modeling Vol. 2 No. 1 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i1.95

Abstract

This article discusses the simulation of planetary movements in the solar system using a linear system-based approach. Mathematical models of solar systems often involve non-linear differential equations, which include the complexity of gravitational interactions between planets and other celestial bodies. However, to simplify the calculation and analysis process, a linear approach can be used with certain assumptions. In this study, the motion of the planets is modeled using Newtonian mechanical principles adapted into a linear equation system. The simulation is carried out by utilizing numerical computing software to calculate the position and speed of the planet in a certain time span. The simulation results show that the linear system approach is able to represent the basic motion of the planet with an adequate degree of accuracy on short time scales, but it shows limitations in predicting complex dynamics, such as orbital resonance or the gravitational influence of small bodies. This approach is suitable for educational applications, where visualization of planetary movements can help understand the basic principles of orbital dynamics. These findings emphasize the importance of choosing the right simulation method according to the purpose, both for scientific and educational purposes. The study suggests the development of a hybrid model that combines a linear approach with non-linear elements to improve accuracy without losing computational efficiency.  
Root Search Applications in Electric Vehicle Cooling Systems Lisa, Ade; Anika
International Journal of Technology and Modeling Vol. 2 No. 1 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i1.103

Abstract

Electric vehicle cooling systems are crucial components that maintain the performance and life of batteries and electric motors through temperature regulation. This research aims to develop a mathematical root search-based application used in the optimization of electric vehicle cooling systems. The methodology used involves mathematical modeling of thermal and fluid flows in a cooling system, followed by the implementation of numerical methods, such as Newton-Raphson and Bisection, to solve non-linear equations related to cooling efficiency. The results show that this application is able to identify optimal operating parameters, such as fluid flow velocity and heat distribution, with high accuracy and efficient computing time. The conclusion of this study confirms that mathematical root search can be applied effectively in the design and operation of electric vehicle cooling systems. The contribution of this research to science includes the development of a systematic approach based on numerical algorithms that can be integrated in thermal simulation software for electric vehicles, thereby supporting innovation in the field of environmentally friendly transportation.
The Role of AI-Powered Chatbots in Telemedicine: Improving Accessibility and Patient Engagement Karim, Mahit Kumaris; Sharma, Rajesh; Singh , Vikram
International Journal of Technology and Modeling Vol. 2 No. 1 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i1.108

Abstract

The integration of Artificial Intelligence (AI) in telemedicine has significantly transformed healthcare accessibility and patient engagement. AI-powered chatbots serve as virtual assistants, providing real-time medical guidance, symptom assessment, and appointment scheduling, thereby reducing the burden on healthcare professionals and improving patient experiences. This paper explores the role of AI-driven chatbots in enhancing telemedicine services by analyzing their capabilities in symptom triage, personalized health recommendations, and patient communication. Furthermore, we discuss the advantages and limitations of AI chatbots, focusing on their impact on remote healthcare delivery, data privacy concerns, and user satisfaction. By evaluating recent advancements and real-world applications, this study highlights the potential of AI chatbots to bridge healthcare gaps, particularly in underserved regions. The findings suggest that AI-powered chatbots can enhance healthcare efficiency, improve accessibility, and foster better patient engagement, paving the way for a more inclusive and technology-driven medical ecosystem.
Next-Generation Autonomous Vehicles Enhancing Safety and Efficiency with Deep Learning Yılmaz, Mehmet; Demir, Ayşe; Kaya, Emre; Çelik, Zeynep; Özkan, Burak; Şahin, Elif
International Journal of Technology and Modeling Vol. 2 No. 1 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i1.110

Abstract

The rapid advancement of deep learning has significantly transformed the development of next-generation autonomous vehicles, enhancing both safety and efficiency. This paper explores the integration of deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and reinforcement learning, in perception, decision-making, and control systems of autonomous vehicles. By leveraging vast datasets and real-time processing, deep learning enables precise object detection, path planning, and adaptive driving strategies. Furthermore, the implementation of sensor fusion techniques combining LiDAR, radar, and cameras enhances situational awareness, reducing the risk of accidents. Despite these advancements, challenges such as computational complexity, adversarial robustness, and ethical considerations remain key research areas. This study provides an overview of the current state-of-the-art deep learning applications in autonomous vehicles and discusses future directions toward fully autonomous, safer, and more efficient transportation systems.
Optimizing Urban Transportation Systems Using Simulation and Modelling Soriano, Nicole Beatrice; Villanueva, Adrian Benedict; Santiago, Erika Mae
International Journal of Technology and Modeling Vol. 2 No. 1 (2023)
Publisher : Etunas Sukses Sistem

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63876/ijtm.v2i1.120

Abstract

The rapid growth of urban populations has intensified the pressure on transportation infrastructure, leading to challenges such as traffic congestion, increased travel time, pollution, and reduced overall mobility. To address these issues, the use of simulation and modelling has emerged as a powerful approach in understanding and optimizing urban transportation systems. This study investigates how various simulation techniques—such as discrete-event simulation, agent-based modelling, and system dynamics—can be applied to analyze traffic patterns, test policy interventions, and predict system behavior under different scenarios. By integrating real-time data and historical trends, simulation models provide a virtual environment for assessing the impact of traffic management strategies, including signal optimization, public transit prioritization, road pricing, and multi-modal integration. The research presents case studies and comparative analyses that highlight the effectiveness of simulation tools in enhancing decision-making processes for urban planners and policymakers. The findings suggest that strategic use of modelling can reduce congestion, improve efficiency, and support sustainable urban mobility. Furthermore, the study emphasizes the importance of interdisciplinary collaboration and the integration of smart technologies to build more resilient and adaptive transport systems. In conclusion, simulation and modelling play a pivotal role in shaping the future of urban transportation in an increasingly complex and data-driven world.

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