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
13 Documents
<![CDATA[Performance Evaluation of Dynamic Radio Resource Allocation for Ultra Dense Networks ]]>
<![CDATA[Reni Silvia Dewi]]>;
<![CDATA[Misfa Susanto]]>;
<![CDATA[Helmy Fitriawan]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 22 No. 1 (2026): Vol. 22, No. 1, March 2026 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v22i1.506
<![CDATA[Ultra-Dense Networks (UDN) offer increased capacity and spectrum efficiency, but the densification of large number of femtocells also triggers complex co-tier and cross-tier interferences. This condition is major challenge in maintaining service quality on 5G and beyond network. This research presents an evaluation of dynamic radio resource allocation performance as an adaptive mechanism to reduce interference in dense UDN environments. Dynamic radio resource allocation selects channels based on minimum interference from neighbouring macrocells to adjust resource allocation to actual channel conditions. Simulations on three macrocells with 210 femtocells per cell show that dynamic radio resource allocation provides consistent performance improvements over conventional scheme. This method increases signal to interference plus noise (SINR) by 8-10 dB, shifts throughput toward higher values, reduces the probability of bit error rate (BER) > 0.01 from 45% to 28%, and reduces network energy consumption by approximately 25-30%. These results confirm that dynamic radio resource allocation is an effective, adaptive, and computationally light approach to improving signal quality and energy efficiency in high-density UDN.]]>
<![CDATA[Analysis of FIR Digital Filter with Optimal Equiripple Design Techniques to Eliminate Jamming in Radar Signal Processing ]]>
<![CDATA[Raisah Hayati Muhammad]]>;
<![CDATA[Yassir]]>;
<![CDATA[Anita Fauziah]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 22 No. 2 (2026): Vol. 22, No. 2, June 2026 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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<![CDATA[Radar (RAdio Detection and Ranging) is a system for detecting and tracking a moving or stationary target using electromagnetic waves. The reflected signal received back by the radar consists of the echo from the desired target and the interference. One form of interference signal that is received back by the radar is jamming. If the interference signal is large enough, it can complicate the process of detecting the desired target. The interference signal can be removed by using a digital filter. This study aims to analyze the effectiveness of a Finite Impulse Response (FIR) digital filter designed using the Optimal Equiripple technique and the Parks–McClellan algorithm for suppressing jamming signals in radar signal processing. The proposed approach was evaluated under different passband frequencies, stopband frequencies, transition bandwidths, filter orders, and signal-to-interference (S/I) ratios to investigate their effects on filtering performance. From the results of the FIR digital filter test using the Equiripple Optimal design technique and the Parks-McClellan Algorithm to eliminate jamming, it was found that the smaller the transition band, the higher the filter order (N), and the maximum S/I value is obtained when the target signal is also lost due to the filter, while the interference signal (jamming) after filtering remains minimal.]]>
<![CDATA[Optimization of PV Array Using Particle Swarm Optimization (PSO) ]]>
<![CDATA[Arya Ramadhan]]>;
<![CDATA[Sri Poernomo Sari]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v21i4.745
<![CDATA[This research investigates the implementation of the Maximum Power Point Tracking (MPPT) method using the Particle Swarm Optimization (PSO) algorithm in photovoltaic systems to optimize output power under various irradiance conditions, including normal, fluctuating, and partially shaded scenarios. The research methodology includes photovoltaic framework modeling and recreation in MATLAB Simulink environment, counting the plan of boost converter to extend output voltage as well as the implementation of PSO calculation to maximize power tracking efficiency. Simulation results show that MPPT with PSO has a higher tracking efficiency than the conventional method, which is 97% under normal and changing irradiance conditions, and 85% under partially shaded conditions. The PSO algorithm proved to be effective in overcoming the local maximum phenomenon in partially shaded conditions. Simulations moreover show that PSO MPPT is able to extend output power significantly compared to ordinary methods. This research contributes to optimizing renewable energy systems, especially in photovoltaic applications, by integrating the PSO algorithm into the MPPT system to increase the efficiency of the energy produced, especially in non-ideal lighting conditions]]>
<![CDATA[Temperature and Humidity Control of The Fermentation Room for Optimization of Cassava Fermentation Process ]]>
<![CDATA[Budi Cahyo Wibowo]]>;
<![CDATA[Ahmad Syakir Ridwan]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v21i4.751
<![CDATA[Cassava fermentation, commonly known as tape singkong, is a fermented product whose success depends on several parameters, including temperature, humidity, and the resulting ethanol content. Therefore, controlling temperature and humidity while monitoring ethanol levels during fermentation is essential. Traditionally, the fermentation process still relies on time estimation, which can reduce quality and slow down production. This study develops a controlled fermentation system using a DHT22 sensor for temperature/humidity monitoring, an MQ-3 sensor for ethanol detection, and a load cell for weight measurement. All sensor data is streamed to the cloud for real-time monitoring. The methodology involves designing and developing hardware and software for temperature and humidity control in the cassava fermentation chamber, calibrating the DHT22, MQ-3, and load cell sensors, and testing system performance. The results show that the DHT22 sensor calibration achieved an accuracy of 98.8% and a precision of 99.6%, while the MQ-3 calibration showed 97.03% accuracy, and the load cell calibration reached 98.6% accuracy. The temperature and humidity control system successfully maintained the fermentation chamber within the 30°C–35°C range. Performance testing confirmed that fermentation with controlled temperature and humidity was 70% faster than conventional methods]]>
<![CDATA[Convolutional Neural Network for Hand Gesture Detection in an IoT-Based Smart Lock System ]]>
<![CDATA[Wandi Ridwansyah]]>;
<![CDATA[Muhammad Hafidz Udzri]]>;
<![CDATA[Qonita Banafsaj]]>;
<![CDATA[Unang Sunarya]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v21i4.755
<![CDATA[In the modern era, security is a major concern, with many cases of theft involving traditional locks. This research aims to develop an IoT-based smart lock system that can be controlled by an android application. The system uses Convolutional Neural Network (CNN) for hand gesture recognition as the control method and TensorFlow Lite for inference on mobile devices. Assessment showed an average accuracy of 96.80% for the closed hand gesture (closing the door) and 96.27% for the open hand gesture (opening the door), with a response time of 0.1 seconds. The system improves efficiency and security and provides easy remote access. Despite challenges such as gesture recognition in low-light conditions, the system provides an innovative solution for improved facility security.]]>
<![CDATA[Optimization of Wireless Sensor Network Node Placement in Oil Palm Plantations using Particle Swarm Optimization for Improved Path Loss Prediction ]]>
<![CDATA[Syahfrizal Tahcfulloh]]>;
<![CDATA[Etty Wahyuni]]>;
<![CDATA[Dwi Santoso]]>;
<![CDATA[Tri Noviyansyah]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v21i4.756
<![CDATA[This study proposes a data-driven framework for optimizing Wireless Sensor Network (WSN) node placement in oil palm plantations on Sebatik Island, Indonesia, by integrating site-specific path loss modeling with a modified Particle Swarm Optimization (PSO) algorithm. Field measurements across 120 transmitter-receiver pairs at 433 MHz revealed that conventional log-distance models poorly predict signal attenuation in dense vegetation (R² < 0.35, RMSE > 8 dB), while calibrated quadratic and cubic polynomial models achieved high accuracy (R² up to 0.9857, RMSE as low as 1.12 dB). These empirical models were embedded into the PSO fitness function to optimize spatial deployment of 20 nodes over a 500 m × 800 m area. The optimized layout achieved 94.7% coverage, 98% connectivity, 42% energy savings over random placement, and 95.6% Packet Delivery Ratio (PDR). Validation against independent field data confirmed robust prediction accuracy (RMSE = 4.3 dB), significantly outperforming generic models like ITU-R. This approach demonstrates that vegetation-aware, empirically calibrated modeling combined with metaheuristic optimization substantially enhances WSN performance in tropical agro-forestry environments, offering a scalable solution for smart agriculture in remote, ecologically complex regions.]]>
<![CDATA[IoT-Based ESP32 System for Real-Time Monitoring of Coffee Fermentation Parameters ]]>
<![CDATA[Istas Manalu]]>;
<![CDATA[Frengki Simatupang]]>;
<![CDATA[Gerry Wowiling]]>;
<![CDATA[Stevi Sianipar]]>;
<![CDATA[Lewi Siagian]]>;
<![CDATA[Jose Raja]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 21 No. 4 (2025): Vol. 21, No. 4, December 2025 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v21i4.757
<![CDATA[Coffee fermentation is a vital stage in the post-harvest process that significantly influences the sensory quality of coffee beans. Through microbial activity, fermentation breaks down the mucilage attached to the beans and produces volatile compounds that shape the final flavor and aroma. This process not only affects organoleptic qualities but also boosts the coffee’s market value, especially in the specialty coffee segment. Therefore, fermentation is essential for farmers, producers, roasters, and consumers, and it also offers opportunities for innovation and research in coffee processing. This study aims to develop and deploy an Internet of Things (IoT)-based coffee fermentation monitoring system with a visual interface using the Blynk platform. The system monitors key fermentation parameters—pH, temperature, and humidity—in real time, enabling a more measurable and consistent post-harvest process. Coffee fermentation is a crucial post-harvest step that determines coffee quality. As fermentation progresses, it helps decompose the mucilage on the beans and produces volatile compounds that influence flavor. Fermented coffee is expected to increase in value, particularly in the specialty coffee market. This makes it vital for farmers, producers, and consumers. During a 48-hour fermentation test, the system successfully recorded a pH change from 6.64 to 3.99, temperatures between 28.1°C and 28.9°C, and humidity levels decreasing from 94.1% to 90.1%. These data indicate active fermentation, consistent with characteristics of a wine coffee production process. Additionally, the Blynk interface allows users to set target values, select fermentation profiles, and remotely view historical graphs. The system also demonstrated stable connectivity and quick response during testing. While the system performed well, some improvements are needed, such as parameter input validation and the addition of an automatic alarm feature. Overall, the system shows great potential for enhancing the efficiency and consistency of coffee fermentation quality, especially for small- and medium-sized enterprises.]]>
<![CDATA[IoT-Based Real-Time Flood Detection and Early Warning System Using JSN-SR04T Ultrasonic Sensor for Urban Areas ]]>
<![CDATA[Muhammad Rusdi]]>;
<![CDATA[M. Sukri Habibi Daulay]]>;
<![CDATA[Ray Kartha Maha Putra]]>;
<![CDATA[Dicky Wahyudi]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 22 No. 1 (2026): Vol. 22, No. 1, March 2026 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v22i1.784
<![CDATA[Flooding is among the most frequent natural disasters in Indonesia, particularly in urban areas such as Medan City. Delays in obtaining flood-related information often result in significant material losses and casualties. This study develops a real-time flood detection and early warning system using the JSN-SR04T ultrasonic sensor integrated with Internet of Things (IoT) technology. The system employs an ESP32 microcontroller to process water level data and transmit information via the Message Queuing Telemetry Transport (MQTT) communication protocol. It categorizes water levels into three statuses: safe (0–110 cm), alert (111–145 cm), and danger (≥146 cm), with automatic alarm activation above 135 cm. Field testing was conducted at Deli River, Medan, an urban flood-prone area. The results showed that the system achieved an average measurement error of 0.96% and a system accuracy of 99.04%, indicating high precision and reliability. Data transmission operated in real time with a response time below 5 seconds and no observed communication failures. Moreover, the use of a 40 mm acrylic tube significantly enhanced sensor stability by reducing fluctuations caused by water surface waves. Overall, the system provides a cost-effective, accurate, and reliable IoT-based flood early warning solution suitable for urban areas vulnerable to flooding.]]>
<![CDATA[Energy-Proportional Modelling of a Dual-Axis Sun Tracker Controller Based on ANFIS ]]>
<![CDATA[Rauzatul Jannah]]>;
<![CDATA[Yuwaldi Away]]>;
<![CDATA[Roslidar Roslidar]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 22 No. 2 (2026): Vol. 22, No. 2, June 2026 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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<![CDATA[The Sun tracker consists of two energy types: proportional energy and operational energy. Proportional energy refers to the clean energy stored in the battery, while operational energy is used to support the mechanical performance of the sun tracking system. One of the main challenges in such systems is the high operational energy consumption, which can reduce the overall system efficiency. This study aims to develop a model to predict the proportional energy resulting from a dual-axis sun-tracker controller by implementing the Adaptive Neuro-Fuzzy Inference System (ANFIS). The method comprises analyzing the performance of the dual-axis sun tracker system and modeling the ANFIS. The performance of the dual-axis was investigated by observing the limitation of servo motor movement based on the difference in LDR sensor readings using threshold values of 50, 100, and 150. The ANFIS modeling was conducted by testing 24 configurations of membership functions to determine the most optimal structure. The results of the threshold value analysis show that a threshold value of 100 provides the best efficiency in generating proportional movement and energy. While modeling the ANFIS, the highest proportional energy was obtained using the Generalized Bell (belief) membership function type with a 9×9 configuration, yielding the lowest error value of 0.011692. Model validation using external test data showed an RMSE of 0.1128 and an MSE of 0.0127, indicating high predictive accuracy and good generalization capability. Implementing ANFIS control on the analyzed dual-axis PV system demonstrated an average increase in the proportional energy efficiency of 3%, from 90% to 93%. The findings indicate the effectiveness of ANFIS in enhancing the performance of the sun tracking system by adaptively adjusting to variations in light intensity.]]>
<![CDATA[Analysis of IoT Communication Performance Using Environmental Sensors in Portable Coffee Bean Dryers Based on Data-Driven Insights ]]>
<![CDATA[Aviq Nurdiansyah Putra]]>;
<![CDATA[Khairul Anam]]>;
<![CDATA[Mohamad Agung Prawira Negara]]>;
<![CDATA[Muchamad Arif Hana Sasono]]>;
<![CDATA[Ferdilla Ayza Melani]]>;
<![CDATA[Bella Inestyas Krisanti]]>;
<![CDATA[Virda Ayu Pujiati]]>
<![CDATA[ Jurnal Rekayasa Elektrika Vol. 22 No. 1 (2026): Vol. 22, No. 1, March 2026 ]]>
Publisher : <![CDATA[Universitas Syiah Kuala ]]>
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DOI: 10.17529/jre.v22i1.1770
<![CDATA[This study presents a data-driven evaluation of Internet of Things (IoT) communication performance in a portable coffee bean drying system by comparing Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT) under identical operational conditions. Environmental data were collected over 54 hours and simultaneously transmitted via both protocols, while local secure digital (SD) card logging served as ground-truth reference. Four key metrics were evaluated: reliability, latency, data consistency, and protocol efficiency. The results show that MQTT achieved higher reliability 91.88% compared to HTTP 81.06%, along with significantly lower average latency 3.87s vs. 15.17s. MQTT also demonstrated superior bandwidth efficiency 91.29% compared to HTTP 13.25%, consuming substantially less hourly transmission data. However, HTTP exhibited higher data consistency, with cloud records more closely matching the ground truth. These findings reveal a clear tradeoff between transmission efficiency and replication accuracy. MQTT is better suited for real-time environmental monitoring in bandwidth-constrained IoT deployments, whereas HTTP provides stronger data integrity at the cost of higher overhead and latency. The proposed parallel, ground-truth-based evaluation framework enables an unbiased and realistic comparison of communication protocols in agricultural IoT systems.]]>
