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INDONESIA
Jurnal EECCIS
Published by Universitas Brawijaya
ISSN : 19783345     EISSN : 24608122     DOI : -
Core Subject : Engineering,
Engineering
EECCIS is a scientific journal published every six month by electrical Department faculty of Engineering Brawijaya University. The Journal itself is specialized, i.e. the topics of articles cover electrical power, electronics, control, telecommunication, informatics and system engineering. The languages used in this journal are Bahasa Indonesia and English.
Arjuna Subject : -
Articles 386 Documents
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A Systematic Literature Review on Machine Learning Techniques for Enhancing Embedded Hardware Reliability Desy Natalia; Cahya Renita Pulse; Rizal Ramadhan; Rama Fahrizal Kusuma; Rizky Ajie Aprilianto; Feddy Setio Pribadi
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

Embedded systems (ES) have played a vital role in industrial automation and critical infrastructure, but their reliability has often been compromised by hardware faults, leading to downtime and safety concerns. Traditional threshold-based fault detection methods have frequently failed to adapt to dynamic environments and have struggled to identify early-stage failures. This study reviewed the effectiveness of artificial intelligence (AI), specifically machine learning (ML) models, for fault detection in ES. A systematic review methodology was employed to analyze the diagnostic performance of several deep learning (DL) architectures, including hybrid convolutional neural network-long short-term memory (CNN-LSTM) models, when implemented on resource-constrained edge devices. The results showed that optimized AI models achieved higher diagnostic accuracy and earlier fault identification compared to conventional approaches. Furthermore, these models enabled real-time, energy-efficient operation on platforms such as Raspberry Pi and ESP32 microcontrollers. It was concluded that AI-driven solutions significantly enhanced predictive maintenance and operational reliability in embedded system applications, demonstrating their transformative potential for future industrial systems.
Monitoring and Controlling System for Ammonia and Methane Gas in Broiler Chicken Farms Using Fuzzy Mamdani-Based Hybrid Junus, Prof. Dr. Mochammad; Saptono, Rachmad; Putri Nabila, Anggraeni
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

The broiler poultry industry significantly contributes to food security by supplying animal protein; however, it also generates harmful gases such as ammonia (NH?) and methane (CH?) from accumulated waste. These gases not only endanger poultry health but also contribute to environmental pollution and climate change. This research proposes the development of an Internet of Things (IoT)-based monitoring and control system for ammonia and methane gas levels in broiler chicken farms. The system employs MEMS NH? and MQ4 gas sensors integrated with an ESP32 microcontroller, and applies the Mamdani fuzzy logic method to classify gas levels into safe, unhealthy, or dangerous categories. Based on the fuzzy output, a water pump powered by a hybrid solar energy system is activated automatically to reduce gas concentrations. Data is transmitted in real-time to a Firebase database and can be accessed via an Android application supporting both manual and automatic control modes. Experimental results demonstrate the system's effectiveness in detecting gas levels accurately and responding efficiently to maintain a healthy farm environment while utilizing renewable energy sources.
Smart Biogas Control for Communities Using Gaussian Naïve Bayes Junus, Prof. Dr. Mochammad; Koesmarjanto; Ria Amanda Salsabella
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

The design and implementation of an intelligent biogas quality monitoring and control system that combines machine learning, actuator automation, and Internet of Things (IoT) technology is presented in this research. The system uses a thermocouple type K, MPX5700, MQ-4, and MQ-135, among other environmental sensors, to measure temperature, pressure, CO?, and CH? in real time. An ESP32 microcontroller processes sensor data using the Gaussian Naïve Bayes algorithm to categorize biogas quality into three classification, namely Good, Moderate, and Poor. A servo motor is utilized to control a valve that either permits or prohibits the flow of biogas to a generator based on the classification output. Through the Blynk IoT platform, the system has the capacity to be remotely monitored. Results from experiments with 40 biogas data demonstrated that the system had good precision and recall in each category and an overall accuracy of 92.5%. The approach exhibits dependability, affordability, and suitability for community-based biogas management in rural and semi-urban evironments.
Design and Performance Evaluation of a PLC- and Fuzzy Logic-Based Control System for Improving Thermal and Humidity Distribution in Cold Storage Environments Sandy Dwi Kurniawan; Mochammad Rusli; Erni Yudaningtyas
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 2 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v19i2.1823

Abstract

Perishable agricultural commodities such as vegetables and fruits are susceptible to environmental storage conditions, particularly temperature and humidity, which significantly impact their quality. This study addresses the critical issue of uneven temperature and humidity distribution in cold storage environments, which can lead to spoilage and reduced product quality. Utilizing Computational Fluid Dynamics (CFD) simulations from ANSYS software, airflow and thermal distribution patterns were analyzed. A fuzzy logic control system was then developed using MATLAB and integrated with a Programmable Logic Controller (PLC) to regulate key actuators—servo motor, fan, and mist maker—based on real-time environmental parameters. Simulation results demonstrated that the fuzzy-controlled system achieved the target temperature setpoint of 21?°C efficiently, with minor fluctuations: ±0.15?°C to ±0.30?°C. The study confirms that intelligent control systems significantly enhance environmental uniformity in cold storage, thereby improving the preservation of perishable goods.
Design of a Monitoring System and Automatic Power Circuit Breaker in Flood Prone Areas Based on the Internet of Things Ferdyanto; Wildan Hakim; Muhamad Alif Razi; Muhammad Raihan Fadhlurrahman
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

Flooding is a natural disaster that occurs due to overflowing water and can cause electrical short circuits in residential areas, endangering the safety of residents and damaging electronic devices. This study aims to design an automatic system for breaking and connecting electrical currents based on the Internet of Things (IoT) that is able to respond to water levels in real-time. The system uses an HC-SR04 ultrasonic sensor and an analog water level sensor connected to an ESP32 microcontroller. When the water reaches a certain limit, the ESP32 will activate the servo motor to cut off the electricity flow to the MCB and send a notification via Telegram. The method used is Research and Development (R&D), including hardware and software design, sensor integration, and system testing. The test results show that the system has a detection accuracy of 98% and is able to cut off or connect the current in less than 2 seconds. Notification delivery runs 100% on a stable network. This system is effective in increasing electrical safety during floods.
Design and Simulation of a 12-Pulse D-STATCOM for Voltage Sag Mitigation and Power Quality Improvement in Unbalanced Distribution Systems Masdi, Hendri; Hasanah, ST., M.Sc., Dr. Rini Nur; Bin Abdul Wahab , Noor Izzri; Husin, Muhammad
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 19 No. 3 (2025)
Publisher : Faculty of Engineering, Universitas Brawijaya

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Abstract

The research introduces a 12-pulse D-STATCOM model developed and simulated to address voltage sag mitigation and power quality enhancement in unbalanced distribution feeders. It tackles critical power quality problems such as voltage depressions, harmonic disturbances, and declining power factor, all of which negatively influence system reliability and efficiency. The 12-pulse arrangement was realized by integrating two 6-pulse Voltage Source Converters (VSCs) through a phase-shifted transformer, which enabled the suppression of dominant low-order harmonics. The overall system was constructed and analyzed in MATLAB/Simulink, where an SRF-based control method was employed to ensure precise reactive power support and rapid voltage restoration. The simulation outcomes indicate notable performance gains: THD decreased from 8.5% in the conventional 6-pulse unit to 3.2%, the power factor increased from 0.85 to 0.98, and the network voltage recovered within approximately 0.02 seconds following a 30% voltage dip. These findings demonstrated that the 12-pulse D-STATCOM provided superior harmonic mitigation, faster dynamic response, and improved system stability compared to the conventional 6-pulse design. The novelty of this study lies in proving that the 12-pulse configuration offers a technically practical yet practically feasible alternative, making it highly relevant for real-world power distribution applications.

Page 39 of 39 | Total Record : 386

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