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Heri Retnawati
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Journal of Robotics, Automation, and Electronics Engineering
Published by Universitas Negeri Yogyakarta
ISSN : 30254590     EISSN : 30253780     DOI : 10.21831
Core Subject : Engineering,
Electrical & Electronics Engineering Engineering
Focus and Scope Subject areas suitable for publication in the Journal of Robotics, Automation, and Electronics Engineering (JRAEE) covering various fields related to, 1. Robotics: - Robot design, kinematics, and dynamics - Motion planning and control of robots - Soft robotics and flexible mechanisms - Human-robot interaction and collaboration - Robot perception and computer vision - Swarm robotics and multi-robot systems - Field robotics and autonomous vehicles 2. Automation: - Industrial automation and smart manufacturing - Process control and optimization - Intelligent control systems and adaptive control - Home and building automation systems - Automation in agriculture and healthcare - Robotic automation in logistics and warehouses - Cyber-physical systems and IoT in automation 3. Electronics Engineering: - Analog and digital circuit design - Microelectronics and VLSI design - Power electronics and renewable energy systems - Sensors and actuators technology - Signal processing and communication systems - Electronic instrumentation and measurement - Wearable electronics and health monitoring devices 4. Artificial Intelligence (AI) in Robotics and Automation: - Machine learning algorithms for robotics - Reinforcement learning for autonomous systems - AI-based decision-making and planning in robotics - Computer vision and image processing in automation - Natural language processing for human-robot interaction - AI-enabled control and optimization in automation - Explainable AI in robotics and automation 5. Mechatronics: - Integration of mechanical, electronic, and control systems - Design and analysis of mechatronic systems - Mechatronic applications in industry and research - Micro- and nano-mechatronics - Intelligent sensors and actuators in mechatronics - Mechatronic control algorithms and strategies - Rapid prototyping and 3D printing in mechatronics 6. Internet of Things (IoT) Technology and Applications: - IoT architecture, protocols, and standards - IoT platforms and frameworks - Edge computing and fog computing for IoT - IoT security, privacy, and trust mechanisms - IoT in smart cities and urban infrastructure - IoT applications in healthcare and telemedicine - IoT for environmental monitoring and sustainability 7. Ethics and Social Implications of Robotics and Automation: - Ethical considerations in autonomous systems - Human-robot interaction ethics - Impact of automation on society and employment - Legal and regulatory aspects of robotics and AI - Privacy and security in robotics and automation - Social acceptance and public perception of robots - Bias and fairness in AI and robotics systems Authors conducting research and investigations within these areas are encouraged to submit their scholarly contributions to JRAEE for potential publication and dissemination of knowledge in these rapidly evolving fields.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2024): March 2024" : 5 Documents clear
Implementation of Kalman Filter With Pi-Controller for Temperature Sensor in Fish Pond Monitoring System Wardah Alfalah; Varlenda Sarma Quraini; Nabilah Qurrotuayun
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.552

Abstract

The research aims to determine monitoring the temperature in fish ponds is crucial for successful cultivation, especially in tropical climates that often experience hot weather. This study proposes an approach using the Kalman Filter method and PI (Proportional-Integral-Derivative). Aside from that, to controller to improve the accuracy of monitoring the temperature in fish ponds. Integration with the Firebase Realtime Database allows for real-time data monitoring. Testing was conducted by comparing the DS18B20 temperature sensor without a filter with three variations of the Kalman Filter and PI controller. The results show that using Kalman Filter 3 with the PI controller resulted in a significant reduction in error and noise compared to using Kalman Filter alone. In conclusion, the integration of the Kalman Filter and PI controller with the Firebase Realtime Database can improve the accuracy of monitoring the temperature in fish ponds and has positive implications for increasing efficiency and fish welfare.
Adaptive Bounding Box Coordinate Adjustment on License Plate Character Detection Using Machine Learning Ahmad Taufiq Musaddid
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.553

Abstract

Effective law enforcement, including the use of the ANPR (Automatic Number Plate Recognition) system, is essential for reducing the number of road traffic accidents. ANPR involves plate localization, character segmentation, and recognition to build a minimum system. This study aims to improve a character segmentation method using a detection approach to address issues like noisy or modified plates. We propose an adaptive improvement on an established sliding window technique, by integrating a CNN (Convolutional Neural Network) for bounding box coordinate adjustment to handle various plate conditions. The proposed method was tested on 280 license plate images and improved the average IoU (Intersection over Union) from 0.4811 to 0.8980. Hence, the recall and precision of the model could be improved to increase any character recognition performance.
Design and Implementation of a Student Counting and Monitoring System in a Laboratory Using Human Tracking Method with OpenCV and TensorFlow Nancy Febriani Taek; Arya Sony
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.554

Abstract

Laboratories serve as crucial facilities supporting practical activities, with a recommended maximum of 20 students, necessitating periodic monitoring to count the dynamic number of students within. The system utilizes the COCO dataset labeled ”person,” involving an approach with entry and exit preference lines, ID identification implementation, and object detection models YOLO v3 Tiny and Faster R-CNN ResNet50. The main system components, Raspberry Pi 3 Model B+, Raspberry Pi Camera 5 MP (f/1.3), and Raspberry Pi 7-inch Touch Display, are integrated for processing, real-time video recording, and image display functions. Test and evaluation results reveal that YOLO v3 Tiny achieves an 88.24% accuracy for entry counting and 75% for entry-exit counting, with an average processing rate of 4.89 FPS, while Faster R-CNN ResNet50 demonstrates lower accuracy, reaching 70.59% and 45.83%, with an average processing rate of 0.58 FPS.
Rotman Lens Size Reduction by Using Same-Size Double Rectangular Defected Ground Structures (DGSs) Method or Same-Size Double Rectangular Slots Method Rizky Hidayat Prasetyo; Eko Tjipto Rahardjo
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.555

Abstract

The need for dedicated communication keeps increasing. A technique to realize that is by using multibeam radiation. A Beamforming Network (BFN) is required to enable multibeam capability in array antennas. This study uses the Rotman Lens as BFN in the frequency of S-Band. The common problem with using Rotman Lens is that its conventional design size is quite large, mainly due to its transition leg ports. Transition leg ports are important to ensure the matching impedance between the lens and the array antenna ports the lens and the beam ports or the lens and the dummy port. The goal of this study is to reduce the size of Rotman lens transition legs by implementing simple and uniform size of slots or Defected Ground Structures (DGSs) methods for the ports of the Rotman Lens BFN. The method can minimize the length of the transition leg and allow the BFN to operate efficiently. The results revealed that the use of the same double-rectangular DGS technique and the same double-rectangular slots in ports can reduce the size of the Rotman lens. Compared to the conventional methods, the proposed method can reduce the size to almost 85 percent from its original size for this S-Band implementation. The other performances of the BFN, besides the size reduction, are not degraded by implementing the proposed methods.
DVFS and Timing Optimization on GPU for Data Center Computation Faris Yusuf Baktiar
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 1 (2024): March 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i1.556

Abstract

Data center computing requires efficient GPU support, both in terms of functionality and power consumption. GPU performance efficiency can be reduced due to high power usage and reduced GPU work stability. So it requires an analysis of computational performance and power efficiency to improve performance and reduce power usage. Core voltage, core frequency, and memory timings are parameters that affect the efficiency of computing performance, power efficiency, and stability. Increasing computational efficiency and GPU power with the effect of modifying parameters can be done through the Basic Input-Output System (BIOS). This study analyzes the efficiency of computational performance by optimizing memory timings and analyzing power efficiency and stability by modifying the DVFS algorithm. Tests are carried out using computational benchmarks commonly used in data centers including the tessellation algorithm, rendering, image processing, pi calculation, image stitching, deep learning, molecular simulation, and N-body. The efficiency of computing performance and GPU power efficiency can be increased by optimizing memory timings and changing the voltage and frequency values on DVFS. Increased performance efficiency ranged from 33.3% to 66.7% and power efficiency increased from 19.9% to 32.6%. Modification of the DVFS voltage state can increase voltage stability and GPU core frequency stability.

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