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JAREE (Journal on Advanced Research in Electrical Engineering)
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 25796216     DOI : https://doi.org/10.12962/j25796216.v4.i2.116
Core Subject : Engineering,
Control & Systems Engineering Electrical & Electronics Engineering
JAREE is an Open Access Journal published by the Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya – Indonesia. Published twice a year every April and October, JAREE welcomes research papers with topics including power and energy systems, telecommunications and signal processing, electronics, biomedical engineering, control systems engineering, as well as computing and information technology.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 175 Documents
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Analysis the Impact of Inset Fed Design with Reference Impedance of Rectangular Microstrip Patch Antenna using Neural Network Fariza, Nadilla; Setijadi, Eko
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.463

Abstract

Abstract -- Research on microstrip antennas is currently growing in prevalence, as their compact design and low cost make them simple to adapt to various needs. The goal of this study is to find out how the inset-fed depth affects the impedance matching of a rectangular microstrip antenna using a simple RMSA design. The author designs the antenna to operate at a frequency of 2.4 GHz with an FR-4 epoxy substrate and simulates it using CST Suite Studio 2019 software. The research shows that adding an inset fed with a depth of 5 mm results in an impedance value of 50.28 + j3.68 Ω, which is close to the desired impedance. The computation process using Neural Network reduces simulation time by 65% faster compared to CST simulation.
Health Monitoring Bracelet based on Internet of Things and Website Alif Razi, Muhamad; Rahayu, Fajar; Firdaus, Naufal
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.382

Abstract

Human mortality rates in the healthcare sector are often attributed to delayed detection of critical health conditions. Vital signs, encompassing metrics like heart rate, blood oxygen levels, and body temperature, play a pivotal role in assessing one's health status and guiding medical interventions. Nevertheless, prevailing vital sign monitoring techniques have limitations, including mobility constraints and reliance on bulky, costly equipment. To address these challenges and enhance physicians' monitoring capabilities, technology-enabled remote sensor readings via the internet are indispensable. However, according to Kominfo, some healthcare facilities, notably in Indonesia, lack internet access, with 3,126 out of 10,133 hospitals and health centers reported as lacking it as of October 2020. To bridge this connectivity gap and enable remote patient monitoring even in internet-deficient settings, this paper presents the design of an Internet of Things (IoT)-based health monitoring bracelet. This innovative bracelet facilitates remote tracking of heart rate, blood oxygen levels, and body temperature. Notably, it can transmit sensor data to a designated website, even in the absence of internet connectivity. Users can conveniently access their measurement data through an intuitive and user-friendly website interface, making this solution a promising tool for enhancing healthcare monitoring, particularly in resource-constrained environments
Integration of the XY-MD02 Module in an IoT-Based Humidity and Temperature Monitoring System with Graphic Display on Nextion LCD Nor, Syafriyadi; Sarifudin, Sarifudin
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.404

Abstract

Abstract—Temperature and humidity monitoring is crucial in various industrial sectors such as agriculture, manufacturing and health. Integrating the latest technology, such as IoT (Internet of Things), opens up new opportunities to increase the efficiency and accuracy of monitoring systems. This research focuses on integrating the XY-MD02 module into an IoT-based monitoring system to measure and monitor humidity and temperature levels accurately. The system uses the XY-MD02 module to collect data, which is transmitted wirelessly to the server using the MQTT protocol. The collected data is processed and displayed in real-time on the Nextion LCD, providing an intuitive graphical representation of environmental conditions. Integrating the XY-MD02 module and Nextion LCD in an IoT-based monitoring system demonstrates practical and reliable humidity and temperature measurements. The average value of the measured temperature is 31.58 with a standard deviation of 0.17, indicating high accuracy in temperature measurement with low variation. Meanwhile, for humidity, the average is 62.34, with a standard deviation of 1.01. The system's compatibility with the MQTT protocol ensures smooth communication and data exchange between devices. Integrating the XY-MD02 module in an IoT-based monitoring system has proven successful in providing accurate and real-time monitoring of humidity and temperature, offering an effective solution in environmental monitoring by keeping up with the latest technological developments. 
Leader-Follower Formation and Obstacle Avoidance for Nonholonomic Mobile Robots Using Velocity Obstacles Putra, Misbah Habib; Agustinah, Trihastuti; Sahal, Mochammad
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.433

Abstract

A multi-robot system is a group of robots that coordinate and perform complex tasks with the help of a communication system. The commonly adapted approaches in multi-robot formation control include the leader-follower method, where the leading robot acts as the coordination center, and follower robots track the movement of the leading robot. Multi-robot formations are usually faced by static and dynamic obstacles in the operational environment. In this paper, the obstacle-avoidance challenge is tackled by adopting the concept of velocity obstacles in a way that enables the robots to efficiently consider not only the velocity of an obstacle but also its direction in order to avoid collision. The method is evaluated through several simulation scenarios in different environments. The simulation results show that the multi-robot formation version can successfully avoid static and dynamic obstacles and reform a formation right afterward from zero collisions.
Optimization Protection Coordination by Optimizing Time Dial Settings at PT. Pupuk Sriwidjaja Palembang Using Grey Wolf Method Januarestu, Achmad Jawahir; Pujiantara, Margo; Priyadi, Ardyono; Jaelani Putra, Riko Satrya Fajar
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 1 (2025): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i1.430

Abstract

Overcurrent Rele (OCR) is an important component in the electric power protection system. One of the parameters that must be set on the OCR is the Pickup Current (Ip) and Time Dial Setting (TDS). To achieve optimum relay coordination by setting the time dial, several optimisation methods have been used such as Genetic Algorithm (GA), Particle Swarm Optimisation (PSO), Fire Fly Algorithm (FA) and Grasshopper Optimisation Algorithm (GOA).In this study, the TDS setting was determined through Using the Grey Wolf Optimisation (GWO) method. The GWO algorithm was able to determine the optimum value of the TDS setting for each OCR process. This is validated by the results of tests conducted using the ETAP application. The primary and secondary relays are able to coordinate effectively to secure three-phase faults that occur on each bus.Furthermore, GWO demonstrated a superior convergence rate in compared to GOA, therefore enhancing its capacity to identify a more optimal TDS setting value. Furthermore, the objective function of GWO is more effective than that of GOA, thereby enhancing its ability to function in a more optimal manner. The results of this test demonstrate that the GWO algorithm is a reliable method for directly identifying the optimal TDS setting value for determining relay coordination settings.Keywords—Protection Coordination Overcurrent Rele ( OCR ), Short Circuit Maximum ( IscMax ), Time Dial Setting ( TDS ), Grey Wolf Optimization ( GWO ).
Diagnostic of generator partial discharge and acoustic imaging scheme for monitoring winding health condition and repair Purnomo, Riyo; Syaputra, Triyadi Nugraha; Suryadiningrat, Rian
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.466

Abstract

Partial discharge in a generator is a phenomenon of electrical discharge that occurs in the generator winding insulation. This phenomenon, if it continues, will cause the generator winding insulation failure. Therefore, partial discharge needs to be monitored, both on-line and off-line. Currently, partial discharge monitoring equipment has been installed at the Cirata Hydroelectric Power Plant (PLTA Cirata), and routine off-line partial discharge testing has been carried out. With this data, it can be used as a reference for the necessary generator maintenance. If the partial discharge trending value increases 2 times in a year, maintenance is required. During maintenance, acoustic imager testing is carried out to map the location of the partial discharge. By combining the three types of testing, a good generator monitoring system will be obtained, and the right type of maintenance will be determined according to the partial discharge mapping results. The analysis begins by conducting on-line and off-line partial discharge trending. If the trending has exceeded the limit, mapping is then carried out with an acoustic imager during maintenance, and repairs are made according to the location and type of damage. Analysis of maintenance results is carried out by comparing the magnitude of the partial discharge value before and after maintenance. The maintenance results based on the test results of the three methods proved effective, this was indicated by a decrease in the off-line PD value from 751.3 nC to 3.792 nC and on-line PD from 23.92 nC to 1.059 nC.
Classification of Diabetic Retinopathy Using ResNet50 Sagala, La Ode Ansyarullah S.; Setiawan, Agung Wahyu
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.436

Abstract

Deep learning has been proposed as an automated solution for classifying the severity levels of Diabetic Retinopathy (DR). In this study, we utilized ResNet50 architecture to classify DR using the APTOS2019 dataset. As an initial step, we initialized the model with pre-trained weights from ResNet50 on ImageNet and implemented augmentation and resampling during training. We adopted an ensemble approach combined with classifiers such as SVM, Random Forest, and Logistic Regression, resulting in a ResNet50-Ensemble (SVM+RF+LR), with outputs obtained using a Soft Voting Classifier. The model achieved an accuracy of 85%, with a precision of 0.72, recall of 0.71, and F1-score of 0.71. The AUC values for the normal, mild, moderate, severe, and proliferative classes were 1.00, 0.96, 0.95, 0.95, and 0.91, respectively, with a Macro-average AUC of 0.96. These findings indicate that the appropriate use of ensemble methods can significantly enhance DR classification performance with suitable optimization strategies.
The Comparison of GAN and CNN Models in the Innovation of Coloring Madura and Bali Batik Permana, Yohan; Kurniawati, Arik; Damayanti, Fitri; Purnawan, I Ketut Adi
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.467

Abstract

This study aims to innovate automatic coloring of batik patterns using deep learning models. Specifically, it compares the performance of Generative Adversarial Network (GAN) with pretrained Caffe-based Convolutional Neural Networks (CNN) in coloring images of Madura and Bali batik. The dataset consists of 388 Madura batik images for training, 97 for validation, and 20 distinct images of both Bali and Madura batik for testing. This dataset was obtained through web scraping from batik posts on social media platforms like Instagram, Bing Image Search using specific keywords, and Kaggle, followed by a manual combination and cleaning process. The GAN model was trained with varying epochs (40, 80, 150), while the CNN utilized pretrained Caffe weights. Evaluation was conducted using Peak Signal-to-Noise Ratio (PSNR), Fréchet Inception Distance (FID), Mean Squared Error (MSE), and Structural Similarity Index (SSIM). The results indicate that the GAN model with 150 epochs outperformed the CNN, achieving a PSNR of 29.702, an FID of 84.016, an MSE of 511.8812, and an SSIM of 0.9925, demonstrating superior color creation and artistic detail in batik. Conversely, the CNN model exhibited lower performance, with a PSNR of 28.218, an FID of 200.271, and an SSIM of 0.7925, indicating its limitations in preserving the intricate patterns and colors of batik. This research demonstrates the applicability of GAN in automatic batik coloring, potentially providing innovative solutions for the batik industry while maintaining the cultural and artistic integrity of traditional designs.
A Stress Level Monitoring System for Rescue Teams During Search and Rescue Operations Based on Electroencephalography hariyadi, dedy; wibawa, adhi dharma; wirawan, wirawan
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.437

Abstract

Search and Rescue (SAR) officers work in high-risk conditions that require physical and mental resilience. Prolonged stress can affect the performance and success of SAR operations. This study evaluates the effectiveness of Electroencephalography (EEG) coherence analysis as a method for monitoring stress in SAR personnel. Using the OpenBCI EEG device and electrodes in the F3 and F4 areas, the brain activity of SAR personnel was recorded in two conditions, office activity (baseline) and rescue operations (SAR condition). The data collection for this research involved the same participants in both baseline and SAR operation conditions, resulting in 30 raw EEG data for further analysis. Data collection on operational conditions was carried out while the rescue officers conducted a search and rescue operation for a capsized boat in the Bengawan Solo River, Ngadirejo Village, Tuban Regency. Data analyzed based on coherence values obtained through the Power Spectral Density (PSD) features of alpha, beta, and gamma sub-band to detect changes related to stress levels. The results showed an increase in coherence in the alpha sub-band by 85.5%, beta sub-band by 92.9%, and gamma sub-band by up to 94.9% during moderate stress conditions, reflecting increased attention, alertness, and intensive information processing required in emergency situations. These findings indicate that EEG coherence analysis can be an effective tool for monitoring stress in SAR personnel in real-time.
Modified an Automatic-Cleaning Strainer for Seawater Cooling System in Combined Cycle Power Plant Purba, Okwaldu; Kusuma, Erryawan; Zhultriza, Ferdiansyah; Kurniawan, Riza
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.468

Abstract

The power plant industries on the coast use seawater as a cooling water system. Seawater conditions in densely populated areas, such as Jakarta, have high levels of pollutants which can affect cooling water systems. To filter seawater from pollutants, a strainer is used due to reliability must be maintained. This research is located at a power plant in North Jakarta. This research describes the latest proposed design of an automatic-cleaning strainer that poses less risk to the system and is faster in the work process. The results of this design were implemented at the generating company. This design can maintain strainer reliability with a faster strainer cleaning process, which reduces the TTR (Time to Repair) in the generating unit from 3 hours to 5 minutes, with no risk of damage to the system due to foreign material in the cooling water system. In addition, the results of this research help improve plant operation and maintenance performance, by increasing EAF 1.11%, increasing 1 level in Maintenance Mix Cost and Manhour from Level 4 to Level 5, increasing Reliability Management by 0.1 level, and also reducing EFOR by 0.98%. Work processes that are carried out automatically via smartphones also contribute to the digitization of the power generation industry to make it more effective and efficient.

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