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Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control
Published by Universitas Muhammadiyah Malang
ISSN : 25032259     EISSN : 25032267     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control was published by Universitas Muhammadiyah Malang. journal is open access journal in the field of Informatics and Electrical Engineering. This journal is available for researchers who want to improve their knowledge in those particular areas and intended to spread the knowledge as the result of studies. KINETIK journal is a scientific research journal for Informatics and Electrical Engineering. It is open for anyone who desire to develop knowledge based on qualified research in any field. Submitted papers are evaluated by anonymous referees by double-blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully within 4 - 8 weeks. The research article submitted to this online journal will be peer-reviewed at least 2 (two) reviewers. The accepted research articles will be available online following the journal peer-reviewing process.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol. 10, No. 2, May 2025" : 12 Documents clear
Design and Simulation of Battery Charging System with Constant Temperature–constant Voltage Method Sudiharto, Indhana; Wahjono, Endro; Sasetyo, Muhammad Yudha; Suryono; Budikarso, Anang
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 2, May 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i2.2194

Abstract

Batteries are essential to many contemporary applications, including electric cars and portable electronics. Overheating and charging time efficiency are the two biggest issues with battery charging. Overheating presents safety hazards and hastens battery deterioration. Due to their inability to regulate temperature, conventional charging techniques like Constant Current - Constant Voltage (CC-CV) result in excessive temperature rises during battery charging, which shortens battery life. A novel approach that helps lessen excessive temperature rises is the Constant Temperature - Constant Voltage (CT-CV) method, according to researchers. In order to avoid excessive temperature increases during the initial charging, the CT technique initially regulates the applied temperature. Second, to guarantee full capacity without causing damage to the battery, the CV technique is used to maintain a steady voltage. A fuzzy logic controller (FLC) control system is used to regulate the temperature and current at the DC-DC converter's output. The FLC control system's goal is to control the duty cycle such that the buck converter's output is 65V 11.5A. The simulation results show that the CT-CV method can reduce the increase in temperature in the battery with an average temperature during the battery charging process of 23.57° C with fuzzy control and 23.71° C with PI control. In addition, by comparing two control systems with the CT-CV method, namely PI and fuzzy, it was found that the fuzzy method was able to accelerate battery charging by 4.16% compared to the PI control.
Optimizing Autonomous Navigation: Advances in LiDAR-based Object Recognition with Modified Voxel-RCNN Firman; Satyawan, Arief Suryadi; Susilawati, Helfy; Haqiqi, Mokh. Mirza Etnisa; Artemysia, Khaulyca Arva; Sopian, Sani Moch; Wijaya, Beni; Samie, Muhammad Ikbal
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 2, May 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i2.2199

Abstract

This study aimed to enhance the object recognition capabilities of autonomous vehicles in constrained and dynamic environments. By integrating Light Detection and Ranging (LiDAR) technology with a modified Voxel-RCNN framework, the system detected and classified six object classes: human, wall, car, cyclist, tree, and cart. This integration improved the safety and reliability of autonomous navigation. The methodology included the preparation of a point cloud dataset, conversion into the KITTI format for compatibility with the Voxel-RCNN pipeline, and comprehensive model training. The framework was evaluated using metrics such as precision, recall, F1-score, and mean average precision (mAP). Modifications to the Voxel-RCNN framework were introduced to improve classification accuracy, addressing challenges encountered in complex navigation scenarios. Experimental results demonstrated the robustness of the proposed modifications. Modification 2 consistently outperformed the baseline, with 3D detection scores for the car class in hard scenarios increasing from 4.39 to 10.31. Modification 3 achieved the lowest training loss of 1.68 after 600 epochs, indicating significant improvements in model optimization. However, variability in the real-world performance of Modification 3 highlighted the need for balancing optimized training with practical applicability. Overall, the study found that the training loss decreased up to 29.1% and achieved substantial improvements in detection accuracy under challenging conditions. These findings underscored the potential of the proposed system to advance the safety and intelligence of autonomous vehicles, providing a solid foundation for future research in autonomous navigation and object recognition.

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