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Andalas Journal of Electrical and Electronic Engineering Technology
Published by Universitas Andalas
ISSN : -     EISSN : 27770079     DOI : -
Core Subject : Science, Education, Engineering,
Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering
Electrical power and energy: Transmission and distribution, high voltage, electrical energy conversion, power electronics and drive. Telecomunication and Signal Processing: Antenna and wave propagation, network and systems, Modulation and signal processing, Radar and sonar, Radar imaging; Radio, multimedia content, Routing protocols, Wireless communications, Signal Processing, Image Processing, Voice Processing. Control automation and Robotic: Robotics, Automation, Pattern Recognition, Biosignal Engineering, Control Theory, Applied Control, System Design, Optimization, Process Control, Sensor. Research in Electrical and Electronic Engineering Education.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 8 Documents
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Search results for , issue "Vol. 5 No. 2 (2025): November 2025" : 8 Documents clear
The Convergence of Artificial Intelligence and Electronic Devices for Rapid Food Quality Measurement: A Systematic Review Mohammad Alfiza Rayesa; Dego Yusa Ali; Neza Fadia Rayesa; Elsa Lolita Anggraini; Togi Siholmarito Simarmata
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.44

Abstract

Ensuring the quality and safety of food is a critical global challenge intensified by complex supply chains and increasing consumer demand for transparency. Traditional measurement techniques—ranging from microbial plating to sensory panels- are often destructive, time-consuming, labor-intensive, and expensive. Recently, non-invasive electronic sensing technologies, coupled with Artificial Intelligence, have emerged as powerful alternatives for rapid and objective assessment. This review aims to identify, synthesize, and appraise peer-reviewed research published between 2005 and 2025 that incorporates AI into electronic devices: electronic noses, computer vision, and spectroscopy for food quality measurement. A systematic literature search was conducted across ScienceDirect, SpringerLink, and IEEE Xplore. The review followed the PRISMA guidelines by identifying 63 studies that met strict inclusion criteria for integrating sensing, hardware, and machine learning algorithms. Analyses show that Computer Vision Systems (CVS), Hyperspectral Imaging (HSI), and Electronic Noses (e-noses) technologies. Deep Learning, in particular Convolutional Neural Networks (CNNs), has surpassed traditional machine learning techniques, such as SVM and PCA, in performance. Key applications include ripeness grading of fruits, detection of adulteration in powders, and freshness monitoring of vegetables and meat products. Integrating AI with electronic sensors provides a scalable, accurate, and non-destructive path forward for Industry 4.0 in the food sector. However, challenges to the issues of model interpretability, data standardization, and real-world robustness remain.
IoT-Based Plant Growth Chamber with YOLOv8 for Anthracnose Disease Severity Classification in Chili Pepper Sutoyo, Mochammad Rizky Abadi; Irman Idris; Gilang Mardian Kartiwa; Muhammad Adli Rizqulloh; Faisal Asadi
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.109

Abstract

Plant growth chambers provide controlled environments for agricultural research, enabling precise monitoring of crop diseases under optimal microclimate conditions. This paper presents an integrated IoT-based smart plant growth chamber system utilizing YOLOv8 machine learning for the automated classification of anthracnose disease severity in chili peppers (Capsicum annuum L.). The system integrates multiple subsystems, including environmental control, a robotic camera with 2-axis movement, a gateway for data communication, and remote monitoring capabilities through a cloud server and a web interface. Dataset labeling was performed using LabelImg and Roboflow, with data augmentation increasing training samples from 70% to 86%. Three YOLOv8 models were evaluated: YOLOv8L (150 epochs), YOLOv8N (100 epochs), and YOLOv8N (398 epochs). Based on our test so far, the YOLOv8L model achieved the best performance with mAP of 67.4% and successfully detected 44 out of 102 test samples (43% detection rate) across multiple disease severity scores (0-9). The system enables both onsite and remote access, automatic data logging, real-time image capture with PyQt5-based GUI, and environmental parameter control (temperature: 5-50°C, humidity: 40-90%RH, light: 0-15,000 lux), which can be manually set and automatically set based on the requirements of the user. This integrated approach demonstrates practical deployment of edge AI and IoT technologies for precision agriculture and disease monitoring applications.
Electrocoagulation in Wastewater Treatment: A Comprehensive Review on Parameters and Applications Nofri Naldi; Hazmi, Ariadi; Reni Desmiarti; Primas Emeraldi
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.163

Abstract

Electrocoagulation (EC) is a widely recognized and effective electrochemical treatment method used for removing various contaminants in liquid wastewater. It is capable of reducing a broad spectrum of pollutants, including heavy metals such as lead and cadmium, fluoride ions, dye molecules, oils, and pharmaceutical residues. The efficiency of EC depends on multiple parameters, including current density (which influences the rate of coagulation), pH level (affecting electrochemical reactions), electrode material (such as aluminum or iron), and the conductivity of the solution (which impacts energy consumption). Compared to conventional chemical coagulation processes, EC offers notable advantages by more effectively destabilizing fine colloidal particles, leading to faster aggregation and sedimentation, while consuming less energy. This review highlights recent technological advancements in EC applications, pointing out that most studies have been conducted at the batch scale, with relatively limited progress in developing continuous operation systems. The main challenges hindering large-scale implementation include electrode passivation (which reduces efficiency over time), sludge management issues, and the need for energy consumption optimization. To address these challenges, various strategies such as improving reactor design, developing hybrid treatment systems, and integrating EC with other processes are being explored. Overall, EC exhibits significant potential as a sustainable, flexible, and cost-effective technology for wastewater treatment. However, ongoing research is crucial to enhance the operational stability of continuous systems and ensure long-term sustainability, thereby facilitating broader industrial adoption of this promising technology.
A Compact Review of Industrial Robots: Dynamic Modeling, Control Strategies, and Operational Challenges Kommey, Benjamin; Stephanie Essah; David Dery Kuusofaa; Samuel Boahene Jnr
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.165

Abstract

When considering Industrial Robots, one often envisions large-scale mechanical systems integrated within manufacturing facilities, specifically designed to transport objects across assembly lines, perform complex assembly tasks, and handle material manipulation with high precision. These robots are capable of performing repetitive and demanding operations, but if proper safety protocols are not implemented, they can pose serious safety hazards to human workers. While these perceptions are accurate, they do not fully capture the complexity and extensive scope of industrial robotics. This review, supported by an exhaustive analysis of numerous technical reviews, academic papers, and research studies conducted over multiple years, synthesizes these findings to provide a comprehensive and sophisticated understanding of industrial robotics. It covers the intricacies of engineering design, including kinematic and dynamic modeling, as well as the development of advanced algorithms and control systems that enable precise, real-time operations. Additionally, it highlights the critical role these robots play in boosting productivity, ensuring operational efficiency, and maintaining consistency in manufacturing processes. With recent advancements in artificial intelligence, new perspectives have emerged regarding control and modeling strategies, paving the way for the development of cognitive robots capable of autonomous decision-making and adaptive behavior, thus opening exciting prospects for the future of industrial automation.
Electro-Mechanical Characterization of Graphite/Epoxy Composites as Potential External-Layer Material for Antenna Radome Aruma, John; Njeri, Waweru; Muguro, Joseph
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.167

Abstract

Graphite is widely recognized in electrical applications for its inherent conductivity. As a reinforcement in composite materials, graphite fibers greatly improve both strength and rigidity, making them ideal for constructing radomes. Traditionally, radomes used in ground and naval settings are made from high-cost materials, such as fiberglass, quartz, and aramid fibers, which are often combined with resins like polyester and epoxy. Nonetheless, issues in structural formation continue to pose challenges. This study aims to investigate the electrical and mechanical properties of graphite/epoxy composites using a dynamic mechanical analyzer (DMA) in double cantilever mode, in accordance with ASTM D7028-07 standards. The objective is to prepare epoxy/graphite composites on a high-density polyethylene (HDPE) substrate with varying composition levels. The study further aims to evaluate the electrical and mechanical properties of electrostatic discharge (ESD) composites using the dynamic materials testing (DMT) method, with a focus on analyzing graphite-epoxy composites as an external layer on antenna radomes. Various specimen types—pure epoxy, surface-coated, and mixed samples with different graphite particle concentrations—were tested at temperatures from 0 to 140°C. A 30V voltage was applied to each specimen, and the resulting current and sheet resistivity were recorded. The electro-mechanical and viscoelastic properties were analyzed, revealing that stress-induced plastic flow occurred in some specimens, accompanied by increased strain energy in graphite-weighted samples. Surface-coated specimens demonstrated distinct behavior, while mixed samples showed a linear strain energy increase up until fracture. Conductivity in epoxy composites was affected by filler content, with conductivity improvements up to a certain filler percentage.
Improve IoT-Based Charging Management System for Electric Vehicles Considering Solar Energy Availability Azizah, Farah; Syafii, Syafii
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.172

Abstract

The decreasing availability of fossil fuels, coupled with escalating environmental concerns, has significantly propelled research and development efforts in renewable energy-based electric transportation systems. The emission of carbon dioxide resulting from the combustion of fossil fuels has prompted the formulation of research policies on electric vehicles (EVs) worldwide, including in Indonesia, where there is a notable increase in EV adoption and a growing demand for enhanced charging infrastructure. Utilizing solar power to charge electric vehicles can substantially decrease carbon emissions when compared to conventional charging methods that draw power from the utility grid. This research endeavors to design, develop, and implement a comprehensive grid-integrated solar-powered EV charging management system that leverages Internet of Things (IoT) technology, with a Raspberry Pi serving as the central control unit. The proposed system will incorporate a pyranometer sensor to accurately measure solar radiation levels and include a sensor to continuously monitor the battery's charging status, specifically the State of Charge (SoC). Through this integrated approach, it is anticipated that the efficiency of EV charging processes can be significantly enhanced, thereby supporting the advancement of sustainable and clean energy infrastructure. Additionally, the implementation of this system aims to contribute to reducing carbon emissions in Indonesia, aligning with national and global environmental objectives.
Optimized High-Gain DC-DC Converter for PV Applications Harmini, Harmini; Titik Nurhayati; Supari; Priyo Adi Sesotyo; Satria Pinandita; Ery Sadewa
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.179

Abstract

Photovoltaic (PV) systems frequently encounter low and fluctuating output voltages, which can significantly impede efficient energy utilization and necessitate more advanced power conversion solutions. Addressing this challenge, the study aims to develop a high-gain DC-DC converter topology that offers stable voltage regulation, making it suitable for PV applications. The proposed solution targets the essential need for substantial voltage boosting while maintaining reliable performance even under varying solar irradiance conditions. The core of the design is based on a Quadratic Boost Converter (QBC) integrated with Voltage Multiplier Cells (VMC), collectively referred to as QBC-VMC. This innovative configuration enhances the voltage gain capability compared to traditional converters. To ensure precise control of the output voltage, a Proportional-Integral (PI) controller is implemented. The system undergoes thorough analysis, including detailed modeling, simulation, and the design of its control structure, to optimize performance. The results demonstrate that the proposed converter can achieve a voltage gain of up to 12 times the input voltage. The PI controller effectively maintains a stable output voltage at approximately 600 V with a tolerable variation of ±0.7%. Additionally, the system exhibits an energy conversion efficiency approaching 81%, even under fluctuating irradiance conditions. This indicates a strong dynamic response and steady-state performance, essential for reliable PV operation. By integrating QBC-VMC with PI control, the proposed approach significantly enhances voltage stability and energy conversion efficiency. Overall, this system provides a promising solution for high-performance PV power systems, capable of delivering reliable power output under varying environmental conditions.
Performance Enhancement of Liquid Filling Process Using Feedforward-Feedback PID Control under DCS Environment Dwi Risdhayanti, Anindya; Ayu Permatasari, Dinda; Rifa'i, Muhamad; Sandra Asti, Irfin
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 5 No. 2 (2025): November 2025
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v5i2.185

Abstract

This study presents the implementation of a Feedforward-Feedback Control method on a Distributed Control System (DCS) Siemens SIMATIC PCS7-based liquid filling process to enhance system stability, response speed, and control accuracy. One of the main challenges in industrial process control is disturbances that cause deviations from the desired setpoint. To address this, a control strategy combining feedforward and feedback actions was developed to anticipate and correct process variations in real time. The system adopts a Multi-Input Multi-Output (MIMO) architecture with two main control variables: liquid level and reactor temperature. Flow rate and liquid level measurements were obtained using the Waterflow YF-S401 and Ultrasonic HC-SR04 sensors, both demonstrating a linear relationship between output voltage and the measured physical quantities, with stable real-time responses displayed on the HMI. The PID controller parameters were tuned using the built-in PID Tuner, yielding Kp = 50, Ki = 150.329, and Kd = 0. Experimental results show that the feedforward-feedback approach reduced the settling time from 78 seconds to 50 seconds and decreased the steady-state error from ±3.8% to ±1.2%. In temperature control, the system successfully reached the operating point of 50 °C with less than 1% steady-state error and a settling time of approximately 60 seconds. The system was configured with AI, AO, DI, DO modules and PROFINET communication, programmed using Sequential Function Chart (SFC) and Continuous Function Chart (CFC). The results demonstrate that the feedforward-feedback control significantly improves process performance and offers strong potential for application in larger-scale industrial automation systems.

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