Jurnal Rekayasa elektrika
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
600 Documents
<![CDATA[Dual-mode Antenna Tracking System for Rocket Launch Applications ]]>
<![CDATA[Fakhri, Muh.]]>;
<![CDATA[Rahmat, Mirza Zulfikar]]>;
<![CDATA[Pascawati, Anita]]>;
<![CDATA[Harsono, Sonny Dwi]]>;
<![CDATA[Nugroho, Yuniarto Wimbo]]>;
<![CDATA[Rahardiyanti, Kandi]]>;
<![CDATA[Rohmah, Nurul Fahrizatul]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 2 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i2.35043
<![CDATA[Rocket launches are complex events that require tracking antennas to maintain a communication link. This study introduces a hybrid tracking strategy that combines manual and program modes by utilizing a predetermined trajectory of the rocket. Automatic switching between tracking modes ensures ongoing monitoring, even during unexpected trajectory changes with the monopulse approach. The dual parabolic antenna arrangement enables this switching. The system estimates the monopulse ratio from the signal strength of each antenna, allowing automatic program tracking to shift to manual mode when reception concerns arise. Performance evaluations included manual, programmable, and dual-mode tests. The system responded to human input and automatically aligned the antenna with slight elevation errors during the initial phase. Adjusting the initial elevation reduced the error. The mode transition was examined by measuring the antenna radiation patterns and monopulse ratio. The systems performance was evaluated in rocket launches, with the rocket trajectory input into the graphical user interface. The antenna exhibited an azimuthal movement of up to 10 , and the ratio fluctuation values remained within the antennas field of view. After 8.8 seconds, the mode switched from program to manual, indicating that the functioning of the systems functioning was stable.]]>
<![CDATA[Control System Design for Water Pump Activation in PLC-based Smart Hydroponic Design ]]>
<![CDATA[Muhammad Edy Hidayat]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 19, No 4 (2023) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v19i4.33443
<![CDATA[Food security is one of the issues that is one of the concerns to the country government, and one of the independent efforts made by community on their awareness to meet and achieve food needs on a domestic scale in their respective households is through hydroponic for cultivation of vegetables. Hydroponics works by using water as growing medium instead of soil, however, the use of water as a planting medium requires special treatment thus the plants is able to grow optimally. To ensure that the air content in the water used as a hydroponic growing medium is properly available, a water regulation process is needed. The process of water regulation in the hydroponic system uses regulation of the activation of the water pump motor so that water can be regulated and electrical energy efficiency can still be achieved. This study aims to design and test a PLC-based automation system for the purposes of setting the activation of a water pump in a hydroponic system based on the sunlight conditions in the hydroponic installation being built. By using a light sensor (LDR) to measure the intensity of sunlight in the hydroponic system being built, the activation of the pump motor can be controlled through the use of a PLC device that processes the information obtained from the sensor used. The results of the tests carried out provide information that the designed system has proven effective for use in hydroponic systems with pump water regulation time from 08:00 AM to 04:00 PM.]]>
<![CDATA[Improved Histogram of Oriented Gradient (HOG) Feature Extraction for Facial Expressions Classification ]]>
<![CDATA[Ramiady, Luthfiar]]>;
<![CDATA[Arnia, Fitri]]>;
<![CDATA[Oktiana, Maulisa]]>;
<![CDATA[Novandri, Andri]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 3 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i3.34044
<![CDATA[Facial expression classification system is one of the implementations of machine learning (ML) that takes facial expression datasets, undergoes training, and then utilizes the trained results to recognize facial expressions in new facial images. The recognized facial expressions include anger, contempt, disgust, fear, happy, sadness, and surprise expressions. The method employed for facial feature extraction utilizes histogram-oriented gradient (HOG). This study proposes an enhancement method for HOG feature extraction by reducing the feature dimension into multiple sub-features based on gradient orientation intervals, referred to as HOG channel (HOG-C). Classifier testing techniques are divided into two methods for comparisonsupport vector machines (SVM) with HOG features and SVM with HOG-C features. The testing results demonstrate that SVM with HOG achieves an accuracy of 99.9% with an average training time of 18.03 minutes, while SVM with HOG-C attains a 100% accuracy with an average training time of 18.09 minutes. The testing outcomes reveal that the implementation of SVM with HOG-C successfully enhances accuracy for facial expression classification.]]>
<![CDATA[Impact of Segmentation and Popularity-based Cache Replacement Policies on Named Data Networking ]]>
<![CDATA[Negara, Ridha Muldina]]>;
<![CDATA[Wasesa, Novan Purba]]>;
<![CDATA[Muhammad, Zaid]]>;
<![CDATA[Mayasari, Ratna]]>;
<![CDATA[Astuti, Sri]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 1 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i1.34309
<![CDATA[The data distribution mechanism of internet protocol (IP) technology is inefficient because it necessitates the user to await a response from the server. Named data networking (NDN) is a cutting-edge technology being assessed for enhancing IP networks, primarily because it incorporates a data packet caching technique on every router. However, the effectiveness of this approach is highly dependent on the router's content capacity, thus requiring the use data replacement mechanism when the router capacity is full. The least recently used (LRU) method is employed for cache replacement policy; yet, it is considered ineffective as it neglects the content's popularity. The LRU algorithm replaces the infrequently requested data, leading to inefficient caching of popular data when multiple users constantly request it. To address this problem, we propose a segmented LRU (SLRU) replacement strategy that considers content popularity. The SLRU will evaluate both popular content and content that has previously been popular in two segment categories, namely the probationary and protected segments. Icarus simulator was used to evaluate multiple comprehensive scenarios. Our experimental results show that the SLRU obtains a better cache hit ratio (CHR) and able to minimize latency and link load compared to existing cache replacement policies such as First In, First Out (FIFO), LRU, and Climb.]]>
<![CDATA[Power Consumption Predictive Analytics and Automatic Anomaly Detection Based on CNN-LSTM Neural Networks ]]>
<![CDATA[Arif Irwansyah]]>;
<![CDATA[Effry Muhammad]]>;
<![CDATA[Firman Arifin]]>;
<![CDATA[Budi Nur Iman]]>;
<![CDATA[Hendhi Hermawan]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 19, No 4 (2023) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v19i4.31695
<![CDATA[In this modern era, electrical energy plays a crucial role in human life, as it is essential for most household appliances. The number of appliances requiring electrical energy increases each year, meeting the growing needs of users. However, electricity consumers tend to forget this fact and only realize its importance when they receive a significantly increased monthly electricity bill or face problems caused by anomalies in electricity use. Such anomalies can lead to substantial losses, especially when electrical equipment is damaged or left switched on without awareness. To make better decisions in such situations, real-time and accurate information is necessary, which can be achieved through data analytics utilizing machine-learning and predictive analytics. The purpose of this paper is to introduce the CNN-LSTM method of data analytic modeling for power consumption data collected through an electric data logger, which can help predict future power usage and detect real-time anomalies in the power network. The proposed model was tested using hourly electricity consumption data, and the results showed that the CNNLSTM method outperformed the LSTM model. The CNN-LSTM model had a 29% smaller Mean Squared Error (MSE) score than the LSTM method.]]>
<![CDATA[IoT-based Monitoring System for Energy Consumption Costs from Battery Supply ]]>
<![CDATA[Hakim, Muhammad Fahmi]]>;
<![CDATA[Kusuma, Wijaya]]>;
<![CDATA[Suudi, Ismail]]>;
<![CDATA[Ridzki, Imron]]>;
<![CDATA[Setiawan, Awan]]>;
<![CDATA[Syamsuri, Tresna Umar]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i4.35237
<![CDATA[A battery must be monitored in real-time to ensure it meets its designed lifetime. Additionally, energy costs from the battery supply must be calculated and controlled to enable solar power plant entrepreneurs to profit practically. This project aims to develop an IoT-based monitoring and controlling system for battery conditions, especially energy consumption costs from battery supply. This system uses an ESP32 microcontroller, INA219 sensor, single channel 5 VDC optocoupler relay, and OLED display. The ESP32 processes the current and voltage from the INA219 sensor and then displays on the OLED display. The parameters displayed include consumed energy costs, current, voltage, power, consumed energy, and used battery capacity. Data is also sent to the Blynk website using IoT, allowing these parameters to be monitored in real time. Based on test results, the average error in calculating energy costs is 0.046%, and other measured or calculated parameters are below 1%. This system can also turn the power flow to the load on and off using the Blynk platform. It can be concluded that the system works well, enabling IoT-based monitoring and control of battery parameters.]]>
<![CDATA[Design and Simulation of Single Input Double Output Coupled Inductor Boost Converter with Bisection Method for Independent Home Application ]]>
<![CDATA[Sudiharto, Indhana]]>;
<![CDATA[Rifadil, Mochammad Machmud]]>;
<![CDATA[Romadhoni, Muhammad Fauzi]]>;
<![CDATA[Milchan, Muhamad]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i4.34086
<![CDATA[This paper proposed a converter design that functions as a voltage booster, increasing the input voltage while supplying two load outputs from a single voltage input using only one switch. Known as a single input double output (SIDO) converter, it aims to enhance power efficieny. The bisection method is employed as an output voltage controller through pulse width modulation (PWM) to achieve an optimal voltage value, adjusted to meet the load requirements. The loads used for independent home applications include a 72 V/12 Ah battery and a 24 V/22 W water circulation pump. The output of the high voltage level acts as a battery charger while the output of the low voltage level serves as an energy supply for the water cir-culation pump. The two loads were chosen because they are widely used, aligning with the goal of realizing independent home applications. The simulation test results showed that the voltage output for battery charging in constant voltage mode was 80.6 V, with an error of 0.0515%, and the voltage output for the water circulation pump was 24 V, with an error of 0.33%.]]>
<![CDATA[Smart Bracelet for Tracking the Location of Dementia Patients ]]>
<![CDATA[Dewi, Ervin Masita]]>;
<![CDATA[Nurmajid, Ikhsan Malik]]>;
<![CDATA[Putro, Trisno Yuwono]]>;
<![CDATA[Kirana, Nurista Wahyu]]>;
<![CDATA[Saefudin, Didin]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i4.40615
<![CDATA[The rising number of dementia patients worldwide is a significant concern. Dementia, marked by deteriorating memory, language, problem-solving abilities, and other cognitive skills, affects millions globally. According to the World Health Organization (WHO), over 55 million people currently live with dementia. Dementia's impact on patients, their families, and healthcare systems is substantial. Patients often need continuous supervision and care, posing challenges for caregivers. Wandering is a frequent issue among dementia patients, leading to safety risks and a high chance of getting lost. Innovative technological solutions, such as portable monitoring devices, are crucial in tackling these issues. A smart bracelet with Global Positioning System (GPS) can be vital for ensuring dementia patients' safety. These devices provide real-time location tracking, giving caregivers and family members peace of mind by enabling them to quickly locate patients who wander off. This makes the bracelet highly effective for monitoring dementia patients' locations, as it will send notifications to a messenger application on a smartphone with a link to the patient's location if they move beyond a 20-meter radius from home. The bracelet uses GPS for distance and location tracking. The patient's location is pinpointed by the intersection of latitude and longitude coordinates. The device has a minimal margin of error, with a latitude error of 0.003% and a longitude error of 0.008%.]]>
<![CDATA[Optimization of Electrospinning Temperature Control System IoT-Based with DHT21 ]]>
<![CDATA[Widayani, Della Astri]]>;
<![CDATA[Hikamiah, Luluk Arifatul]]>;
<![CDATA[Nugroho, Panji Setyo]]>;
<![CDATA[Ariyanto, Dewa Pascal]]>;
<![CDATA[Amaratirta, Jasmine Cupid]]>;
<![CDATA[Harjunowibowo, Dewanto]]>;
<![CDATA[Rezeki, Yulianto Agung]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i4.37537
<![CDATA[Electrospinning is a method of making nanomaterials that has a fairly easy and flexible process that can produce nanofiber continuously. Nanofiber morphology from the electrospinning process is influenced by several parameters, one of them is temperature as an environmental parameter. If there is no temperature control system in the electrospinning system, it will be difficult to maintain the consistency of the morphology nanofiber and at certain temperatures, nanofibers are not formed. Therefore, this study aims to develop a temperature control system for electrospinning called the Electrospinning Temperature Control (ETC) System and connect it with an internet-of- things (IoT) platform to understand the dynamics of the temperature control process, upload temperature data to the cloud, and remote monitoring. The method used by designing and building system hardware and software, calibrating DHT21 as a temperature sensor and testing system performance. The results show that the calibration of the DHT21 sensor has an accuracy rate of 94.95% and a precision rate of 98.93%, while the results of the performance test show that the system can raise, maintain, and lower the temperature. Further performance testing reveals that the ETC system can operate within a temperature range of 2040C. The IoT system using the Blynk App allows users to remote and monitor easily, and using Google Sheets as a cloud database. The ETC system was successfully built and can be applied to electrospinning experiments.]]>
<![CDATA[Optimizing Palm Oil Plantation Productivity Using Offline Blockchain and Drone Rover Solutions ]]>
<![CDATA[Aryanto, Aryanto]]>;
<![CDATA[Cipta, I Nengah Marccel Janara Brata]]>;
<![CDATA[Putri, Dinda Armeylia]]>;
<![CDATA[Amelia, Bella]]>;
<![CDATA[Pratama, Muhammad Herly]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol 20, No 4 (2024) ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v20i4.40676
<![CDATA[The increasing demand for sustainable palm oil production challenges plantations to maintain efficient management and data transparency, particularly in remote areas with limited internet access. This study aims to develop and implement an offline blockchain system integrated with drone rover devices to support data collection and decision-making without internet connectivity. Drone rovers equipped with sensors and cameras are deployed to collect comprehensive data on plant health, pest detection, and environmental conditions across the plantation. The offline blockchain securely stores this data, ensuring integrity and traceability. Additionally, an AI system is utilized to process this data in real-time, enhancing the precision of monitoring plant health and fruit ripeness. Results indicate that this approach optimizes resource management, improves operational transparency, and enables accurate decision-making in palm oil plantation management. By combining offline blockchain technology with AI-driven analysis, this study provides a scalable and effective solution for sustainable agriculture in connectivity-challenged environments.]]>
