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Contact Name
Elizar
Contact Email
jre@unsyiah.ac.id
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+62651-7554336
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jre@unsyiah.ac.id
Editorial Address
Jurusan Teknik Elektro dan Komputer Gedung A2 Lt. 2 Fakultas Teknik Jalan Syech Abdul Rauf no. 7 Kopelma Darussalam 23111
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Kab. aceh besar,
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INDONESIA
Jurnal Rekayasa elektrika
ISSN : 14124785     EISSN : 2252620X     DOI : https://doi.org/10.17529/hre.v19i1.15128
The journal publishes original papers in the field of electrical, computer and informatics engineering which covers, but not limited to, the following scope: Electronics: Electronic Materials, Microelectronic System, Design and Implementation of Application Specific Integrated Circuits (ASIC), VLSI Design, System-on-a-Chip (SoC) and Electronic Instrumentation Using CAD Tools, digital signal & data Processing, , Biomedical Transducers and instrumentation, Medical Imaging Equipment and Techniques, Biomedical Imaging and Image Processing, Biomechanics and Rehabilitation Engineering, Biomaterials and Drug Delivery Systems; Electrical: Electrical Engineering Materials, Electric Power Generation, Transmission and Distribution, Power Electronics, Power Quality, Power Economic, FACTS, Renewable Energy, Electric Traction, Electromagnetic Compatibility, High Voltage Insulation Technologies, High Voltage Apparatuses, Lightning Detection and Protection, Power System Analysis, SCADA, Electrical Measurements; Telecommunication: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network; Control: Optimal, Robust and Adaptive Controls, Non Linear and Stochastic Controls, Modeling and Identification, Robotics, Image Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligent and Expert System, Fuzzy Logic and Neural Network, Complex Adaptive Systems; Computer and Informatics: Computer Architecture, Parallel and Distributed Computer, Pervasive Computing, Computer Network, Embedded System, Human—Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods), Programming (Programming Methodology and Paradigm), Data Engineering (Data and Knowledge level Modeling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data), Network Traffic Modeling, Performance Modeling, Dependable Computing, High Performance Computing, Computer Security, Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Information Retrieval, Intelligent System, Distributed Computing System, Mobile Processing, Next Network Generation, Computer Network Security, Natural Language Processing, Business Process, Cognitive Systems. Signal and System: Detection, estimation and prediction for signals and systems, Pattern recognition and classification, Artificial intelligence and data analytics, Machine learning, Deep learning, Audio and speech signal processing, Image, video, and multimedia signal processing, Sensor signal processing, Biomedical signal processing and systems, Bio-inspired systems, Coding and compression, Cryptography, and information hiding
Articles 6 Documents
Search results for , issue "Vol 21, No 1 (2025)" : 6 Documents clear
Wood Species Identification Based on Gray Level Co-Occurrence Matrix (GLCM) Features on Macroscopic Images Ilham Ramadhan, Muhammad Ghiffaari; Sugiarto, Bambang; Dwi Mulya, Okta; Septian Chairulsyah, Defti; Syahrizal, Adyanto; Gunawan, Gunawan; Haviani Laluma, Riffa; Nuraini Sukmana, Rini; Wiharko, Teguh
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.41078

Abstract

Wood is an incredibly valuable resource, particularly for everyday living. To fully harness the advantages of wood, it must focus on two key considerations. Firstly, it is imperative to consistently utilize wood sourced from sustainably managed forests. Secondly, we must explore techniques that maximize the utilization of every part of the tree. One technique for meeting these considerations is to create a wood identification system. This system can be used for quickly inspecting wood species. In wood identification, it is essential to consider specific characteristics and physical properties of wood. Manual identification will depend on the examination of wood anatomists eye and will require a significant amount of time. In accordance with these situations, a computer vision-based system can address this condition. Therefore, feature extraction is necessary to extract the features of wood characteristics from the wood image. This research aims to propose a method for wood species identification based on Gray Level Co-occurrence Matrix (GLCM) features to extract important information about wood characteristics from macroscopic wood images. For the classifier, the Random Forest algorithm is proposed for the identification of the machine learning model. Five wood species images will be used in this research, with each wood sample being presented as a macroscopic image. The total dataset used was 750 images, with each wood species having 150 images. The result showed that the Model C (90/10) training data ratio demonstrates good performance in classifying wood species from the macroscopic images. The model achieved a peak accuracy of 0.81 and correctly predicted all test images. This study indicates that the Random Forest model can be an effective classifier for wood species identification.
Positioning Control System on the Movement of Wheeled Humanoid Robot Using Swerve Drive Model Based on Fuzzy Logic Controller Harry, Caroline; Amirulsyah, Ahmad Rizky; Hermawati, Harmawati; Dwijayanti, Suci; Suprapto, Bhakti Yudho
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.36393

Abstract

Technology in robotics has developed rapidly in the last few decades, as evidenced by the increasing number of robots created, such as humanoid robots and mobile robots. In this study, a wheeled humanoid robot is designed to move from one place to another using a swerve drive model, a holonomic type of drive wheel. This model uses a combination of DC motors and gears to ensure smooth movement of the humanoid robot. The swerve drive allows the robot to move freely in all directions. Therefore, the humanoid robot requires a control system to manage and automatically regulate the state of the system. The fuzzy logic control system can perform mathematical calculations based on human knowledge, serving as a controller without requiring a mathematical model of the controlled process. The results obtained from this study demonstrate the robots ability to move stably and accurately, based on the response to the rules provided by the fuzzy logic control system. The more membership functions used, the more stable and accurate the results will be, while using fewer membership functions will result in faster response times to reach the setpoint.
Water Quality Monitoring and Control System in Koi Fish Cultivation Based on Internet-of-Things (IoT) Ahmad, Ali Hanafi; M.Yanis, Naili Ikrimah; Nur Irawan, Muhammad Naufal; Munadi, Rendy; Fitriyanti, Nurwulan
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.40760

Abstract

This research develops an Internet-of-Things (IoT)-based system for real-time monitoring and automatic control of water quality in koi fish farming, addressing the lack of knowledge regarding optimal water conditions. The system integrates sensors for pH, ammonia, temperature, total dissolved solids (TDS), and turbidity, along with controllers such as filters, coolers, and heaters, all managed through a mobile application called AquaKoi. System testing is divided into IoT device testing and mobile application testing. IoT device testing ensures proper sensor and controller functionality, with sensor data verified against water quality standards. Application testing includes black box testing, quality-of-service (QoS) measurement, user acceptance test (UAT), and notification warning testing, showing a user satisfaction rate of 92%. The test results indicate that the system functions well and meets specifications, despite challenges like overheating of the ESP32 microcontroller, which was mitigated with a temporary fan solution. Overall, the AquaKoi system demonstrates significant potential in enhancing the efficiency of koi fish farming. However, further development is recommended to address technical constraints, improve the user interface, and expand the systems capabilities to meet more diverse user needs.
A Comparative Study of the Implementation of 4G and 5G Networks in IIoT Process Automation Systems Wardana, Awang Noor Indra; Putra, Iqbal Aliandra; Muhammad, Fawwaz Afif
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.40928

Abstract

The industrial internet-of-things (IIoT) has recently become an important requirement in the process industry. The factories must be able to integrate process automation devices such as programmable logic controllers and industrial computers with mobile devices, especially to support their maintenance and operations. Connectivity with mobile devices has the consequence that cellular networks must be specified to the needs of the industry itself. Comparative studies on using cellular networks in process automation systems are urgently needed. The research that has been conducted is a comparative study between the use of 4G and 5G cellular networks in IIoT process automation systems. It can be seen in the result that the 4G cellular network is sufficient to be used for industries that require mobile devices for monitoring functions, as seen from the results showing the latency obtained is 17.03 ms, jitter is 9.5 ms, packet loss is 6.67 %, and throughput is 192.73 Kbps. However, for the industry that needs to perform real-time control, mobile connectivity has to use a 5G network with better performance metrics with a latency of 15.21 ms, jitter of 5.43 ms, packet loss of 2.67 %, and throughput of 217.19 Kbps. The research results are needed by the process industry in Indonesia, which is widely spread on the island as an archipelago with quite varied cellular network connectivity quality.
Integration of Multi-Modal Sensors and Robot Arm Vision for Monitoring and Assisting Elderly Activities Jura, Suwatri; Jalil, Abdul
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.41273

Abstract

This research aims to develop an integration device combining Multi-Modal Sensors and Robot Arm Vision (MMS-RAV) for monitoring activities and assisting in healthcare services for the elderly at home. The method used to develop this device involves integrating MMS, which consists of PIR sensors for detecting the presence of the elderly, LDR sensors for detecting home light conditions, fire sensors for detecting flames, and DHT11 sensors for measuring temperature and humidity. Additionally, the RAV component assists and supports the activities of the elderly and includes a camera for vision-based object detection, ultrasonic sensors for robot navigation, Raspberry Pi as the data processing center, an arm for object retrieval and camera movement, LCD for displaying messages, omni-wheels for robot navigation, and buzzer for early warnings in case of anomalous conditions with the elderly. In this research, MMS functions to monitor elderly activities, while RAV supports healthcare services for the elderly, particularly in medication intake using image processing techniques. The software used to control the entire MMSRAV system is the robot operating system. The results of this study indicate that the developed MMS-RAV device is effective for monitoring elderly activities and assisting in providing healthcare services for medication intake.
Implementation of Eye-To-Text Morse Code Device to Help Speech Impairments People Wahyuningsih, Pujianti; Matalangi, Matalangi
Jurnal Rekayasa Elektrika Vol 21, No 1 (2025)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v21i1.41268

Abstract

This research aims to develop an Eye-to-Text Morse Code (ETT-MC) device as an assistive communication tool for individuals with speech disabilities, based on artificial intelligence image processing. The method used to detect speech codes is based on eye blink input, which is converted into Morse code and then translated into letters by utilizing a thresholding image processing technique that compares the pixel values when the eyes are open and closed. In Morse code, there are two main symbols combined to form a letter: the dash and the dot. The object of this research is the eye, where if the system detects the eye in an open state, it is converted into a dot code or value 1, while when the system detects the eye as closed, it is converted into a dash code or value 0. The results and hypotheses of this research show that the developed ETT-MC device can assist individuals with speech disabilities in communicating by utilizing eye blinks as an input medium to convey messages to others with an accuracy rate of up to 80%. This occurs because the accuracy of eye image detection processed by the system is significantly influenced by light intensity, the quality of the image detected by the camera, and the length of the translated text.

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