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Emitor: Jurnal Teknik Elektro
Published by Universitas Muhammadiyah Surakarta
ISSN : 14118890     EISSN : 25414518     DOI : https://doi.org/10.23917/emitor
Core Subject : Engineering,
Engineering
Emitor: Jurnal Teknik Elektro merupakan jurnal ilmiah yang diterbitkan oleh Jurusan Teknik Elektro Fakultas Teknik Universitas Muhammadiyah Surakarta dengan tujuan sebagai media publikasi ilmiah di bidang ke-teknik elektro-an yang meliputi bidang Sistem Tenaga Listrik (STL), Sistem Isyarat dan Elektronika (SIE) yang meliputi Elektronika, Telekomunikasi, Komputasi, Kontrol, Instrumentasi, Elektronika Medis (biomedika) dan Sistem Komputer dan Informatika (SKI).
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 16 Documents
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Search results for , issue "Vol 25, No 3: November 2025" : 16 Documents clear
Design and Development of a Mobile-Based Application Path Planning System for Autonomous Electric Vehicles with Ant Colony Optimization Algorithm Sari, Melia; Windi Sari, Desi; Kurniasari, Puspa
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13101

Abstract

The rapid advancement of technology has generated numerous innovations across various domains, including transportation. One notable development is the autonomous vehicle, a driverless system capable of navigating to a designated destination without human intervention. This study emphasizes two critical aspects: navigation and efficient path planning. The objective is to design and develop a mobile application for optimal path planning based on the Ant Colony Optimization (ACO) algorithm. The application was developed using Visual Studio Code as the integrated development environment (IDE) and implemented under the waterfall software development model. The ACO algorithm served as the core mechanism for path determination, supported by the Google Maps API to provide spatial data required for processing. Additionally, Firebase was employed for user authentication—such as registration and login—and for storing trip history. Testing results indicate that the developed mobile application successfully operates according to its intended functions. In particular, the system demonstrates the capability to determine the shortest path effectively through the implementation of the Ant Colony Optimization algorithm. These findings suggest that the proposed approach can support advancements in autonomous vehicle navigation systems by offering efficient and reliable path planning solution
DGA–Duval Triangle Analysis for Early Thermal Fault Diagnosis of Transformer Oil Muhtar, Ali; Azizah Umar, Ismi
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13359

Abstract

This study assesses the health of the T5 transformer oil at the Geothermal Power Plant to enable early thermal-fault diagnosis and support evidence-based maintenance. Methods comprised Dissolved Gas Analysis (DGA) with TDCG evaluation per IEEE C57.104-2019, Duval Triangle mapping, and breakdown-voltage (BV) and water-content testing per IEEE C57.106-2015. Results show TDCG of 686 ppm (Condition 1) with CO₂ at 10,000 ppm; gas fractions CH₄ 70.18%, C₂H₄ 29.24%, and C₂H₂ 0.58% place the point in zone T2 (300–700 °C). Water content is 29 ppm—above the recommended limit for transformers <72.5 kV (good: <10 ppm)—while mean BV is 73.4 kV, exceeding the 40 kV minimum. The evidence indicates a medium-level thermal fault with high moisture contamination. Oil filtering/dehydration and periodic DGA trend monitoring are recommended to mitigate failure risk and inform data-driven maintenance planning
4-DoF Robotic Arm for Picking and Moving RGB Color-Based Objects Using the Support Vector Machine Method Rendyansyah, Rendyansyah; Irmawan; Caroline
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13552

Abstract

This study discusses designing and implementing an RGB color pattern recognition system using the Support Vector Machine (SVM) method on a 4-DoF robotic arm to perform autonomous object transfer tasks. This system integrates computer vision, artificial intelligence, and trajectory planning technologies to improve the adaptability and precision of the robot manipulator's movements. The pattern recognition process is done through image acquisition using a camera mounted on a support pole, then extraction and normalizing color values in the R, G, and B channels. These RGB values are input features for color pattern classification using SVM with Radial Basis Function (RBF) kernel and regulation parameter C = 100. The training results show that the SVM model can classify three color classes (red, yellow, and blue) with an accuracy rate of 100%. The classification data is then used to control the movements of three robots with red, orange, and blue arms, each tasked with picking up and moving objects of the corresponding color. The robot trajectory was planned using the Cubic Trajectory method, which produced smooth and coordinated movements between joints, with an average task completion time of ±10 seconds. Based on the results of 30 trials, the system showed a success rate of 96.67%, with only one failure due to gripper position inaccuracy. The results of this study indicate that the combination of the SVM and Cubic Trajectory methods can improve the efficiency and accuracy of robotic arm systems in color-based object recognition and manipulation, which has the potential to be applied to artificial intelligence-based industrial automation systems.
Design of an Arduino-Based Inverse Type Overcurrent Relay susilo, rizky; Marselino Pakorong; Priyo Handoko Chusnama Ali
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13676

Abstract

Abstract An overcurrent relay is an important device in protection systems to protect electrical equipment from damage caused by excessive overcurrent. The objective of this study is to design and implement an overcurrent relay system that can detect and mitigate overcurrent using the inverse time protection principle, developed using the popular and accessible Arduino platform. An overcurrent relay (OCR) is an electrical protection device that operates based on overcurrent detection. There are two main characteristics, namely inverse time and constant time.Inverse Time Relay cuts off overcurrent with an operating time that increases as the current increases, while Constant Time Relay has a fixed operating time. This research discusses the working principles, differences in characteristics, and applications of both types of relays to improve the effectiveness of protection in electrical power systems.
Design and Implementation of a Negative Ion Generator Based on MQ-135 Sensor and Arduino Nano Gunastuti, Dwi Anie; M. Lanny W. Panjaitan, M.; Lukas, Lukas
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13673

Abstract

This paper presents an enhanced study on the design, modeling, and implementation of a Negative Ion Generator (NIG) based on the MQ-135 air-quality sensor and Arduino Nano microcontroller. The research combines theoretical modeling of corona discharge, electric field dynamics, and Cockcroft–Walton (C–W) voltage multiplication with experimental validation. Measured pollutant reductions ranged between 25–40% within 10 minutes of ionization, correlating well with theoretical predictions [1]. The proposed smart NIG offers low-cost, energy-efficient, and automated operation suitable for modern indoor environments, contributing to the development of intelligent IoT-based air-quality systems [2]
Impact of Noise on Fault Classification in High-Voltage Transmission Lines Using LVQ Neural Networks Hardiyanti Mursat, Marta; Novizon, Novizon; Sulthanah, Hana
Emitor: Jurnal Teknik Elektro Vol 25, No 3: November 2025
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/emitor.v25i3.13620

Abstract

Accurate fault detection and classification in high-voltage transmission lines are essential to ensure system reliability and operational safety. However, the presence of noise and transient disturbances often degrades the accuracy of conventional protection schemes. This study investigates the impact of Gaussian noise on fault classification performance using a neural network-based framework combined with Discrete Wavelet Transform (DWT) and Fast Fourier Transform (FFT) feature extraction. Four types of faults, single line to ground, line to line, double line to ground, and three phase to ground were simulated on a 150 kV transmission system using ATPDraw under various noise levels 40 dB. Linear Discriminant Analysis (LDA) and Learning Vector Quantization (LVQ3) were employed for feature reduction and classification, respectively. The proposed model achieved a test accuracy of 98.84% under free noise conditions and 96.80% under noisy conditions. This is outperforming traditional classifiers such as Support Vector Machine (SVM) and Decision Tree (DT). Results indicate that incorporating time-frequency domain features with noise-resilient neural architectures significantly enhances classification robustness and reliability. This research contributes a novel approach for noise-tolerant fault classification, offering practical potential for real-world implementation in intelligent protection systems and smart grid applications.

Page 2 of 2 | Total Record : 16

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