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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 81 Documents
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Evaluation of ANN Training Methods: A Comparative Study of Back Propagation, Genetic Algorithm, and Particle Swarm Optimization for Predicting Electrical Energy Consumption Prenata, Giovanni Dimas
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.v25i3.12719

Abstract

This study compares the performance of ANN with three training methods: Backpropagation (BP), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) in a simple classification case. The results show that ANN GA has the smallest average error (0.0308), followed by ANN BP (0.0569), while ANN PSO is much larger (0.7559). Thus, ANN GA proved to be the most stable and accurate, ANN BP still performed quite well, while ANN PSO had the weakest performance.
Design of a Ship Speed Control System Using Hybrid Propulsion Based on Fuzzy Logic Aldoko, Fajar Surya Muhammad; Kurniawan, Edi; Amrullah, Romanda Annas; Nurdiansari, Henna; Sandi, Wulan Marlia
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.v25i3.12727

Abstract

The maritime transportation sector, especially in archipelagic countries like Indonesia, faces significant challenges in optimising ship speed and fuel efficiency, particularly when using hybrid propulsion systems. This study aims to design a ship speed control system based on fuzzy logic integrated with a hybrid propulsion system (BLDC motor and diesel engine) for a trimaran vessel. The research employed both static and dynamic testing on the system, measuring parameters such as motor RPM, current consumption, voltage, and fuel efficiency across different speed modes (from 4 km/h to 11 km/h). The results showed that the fuzzy logic-based control system notably improved speed stability and fuel efficiency, especially at lower speeds, compared to conventional systems. Additionally, the system effectively adapted to environmental conditions such as waves and currents, optimising power distribution between the BLDC motor and diesel engine. The conclusion emphasises that this fuzzy logic-based control system offers a promising solution to enhance operational efficiency in hybrid propulsion systems for maritime vessels, ensuring reduced fuel consumption and improved environmental sustainability.
Design and Development of an EMG-Based Interactive Musical Instrument Using the Decision Tree Method Pratiwi, Reniantika Dwi; Rokhana, Rika; Waya Rahmaning Gusti, Agrippina
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.v25i3.12866

Abstract

Hand motor limitations often hinder individuals from expressing their musical creativity, particularly those affected by neurological disorders, musculoskeletal injuries, or playing-related musculoskeletal disorders. Such impairments restrict access to traditional instruments and highlight the need for alternative modes of musical interaction. This study addresses the problem by designing an interactive musical instrument based on surface electromyography (EMG), enabling the conversion of forearm muscle activity into digital notes via a MIDI controller in real time. The system integrates a Muscle Sensor v3, Arduino Uno, and Python-based software equipped with a graphical user interface. The processing pipeline consists of EMG signal acquisition, feature extraction using three widely adopted time-domain features—Mean Absolute Value (MAV), Root Mean Square (RMS), and Waveform Length (WL)—and gesture classification with a Decision Tree algorithm implemented in scikit-learn. Once classified, the gestures are mapped to corresponding MIDI note values and transmitted to a Digital Audio Workstation (DAW) for sound production. Experimental evaluation was performed on eight distinct hand gesture classes. For each class, 20 repetitions were collected for training, and 10 additional repetitions were used for testing, resulting in 80 independent test trials. The system achieved an overall accuracy of 82.5%, with 66 correct predictions out of 80. Simple gestures such as Hand Open and Index Bend reached 100% accuracy, whereas gestures with overlapping muscle activation patterns, notably Form Number 1 and Form Number 2, achieved only 60% accuracy due to their highly similar EMG features. These results demonstrate that the Decision Tree algorithm, while computationally efficient and interpretable, has limitations when handling non-linearly separable data. Nonetheless, the study establishes the feasibility of using Decision Trees as a lightweight baseline for real-time EMG-based musical interfaces. The findings suggest potential for further development through multi-subject, multi-channel EMG datasets and advanced classifiers such as Support Vector Machines (SVM) or Artificial Neural Networks (ANN). Ultimately, this work contributes to the advancement of inclusive and adaptive digital musical technologies for individuals with motor impairments.
Detecting of Gunshots Direction Using TDOA (Time Difference of Arrival) Untsa, Risdilah Mimma; Akbar, Fannush Shofi; Faradila Purnama, Arrizky Ayu; Muhsin, M; Rachmaningrum, Nilla
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.v25i3.12867

Abstract

In order to avoid shots being fired in undesirable areas, a device is required that can detect the origin of the shot so that the source of the bullet can be identified. This research was conducted to maintain the security and stability of a region. The objective of this study is to develop a device that utilizes the time difference of arrival (TDoA) method to determine the direction of gunshot on a gunshot location device. Prior to the implementation of TDoA, the received sound undergoes a filtration process utilizing an FIR filter. The filtered sound is then subjected to the time-of-arrival (TDoA) method. This method involves the comparison of the direction of sound arrival, followed by calculation and conversion to determine the origin of the gunshot sound. The TDoA coordinates are subsequently determined through the utilization of the multilateration method. In the experiments conducted using a speaker as the sound source and four microphones as receiving sensors, changing the speaker's location demonstrated that the signal-to-noise ratio (SNR) of the sound signal increased as the distance between the sensor and the sound source decreased. Furthermore, the implementation of an FIR filter during post-processing can enhance the SNR of the sound received at the sensor by 27% to 32%. In this research, the TDoA method demonstrated a high degree of efficacy, attaining a detection accuracy of 99.78%.
Design and Performance Evaluation of an Energy Efficient Manure Shredder Pulverizer for Organic Fertilizer Production Damayanti, Annisa Maulidia; Amalia, Zakiyah; Permatasari, Dinda Ayu; Wicaksono, Rendi Pambudi; Hasanah, Qonitatul; Puspitasari, Etik
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.v25i3.12977

Abstract

The growing demand for organic fertilizer calls for innovations in manure processing technology to enhance production efficiency and product quality. This study presents the design, fabrication, and performance evaluation of a prototype manure shredder–pulverizer that integrates dual shredding and pulverizing functions to accelerate the composting process and produce uniform particle sizes. The machine is powered by a 6.5 HP gasoline engine and tested using fresh goat manure with an average moisture content of approximately 70%. Performance evaluation focused on processing capacity, particle size distribution, specific energy consumption, and output homogeneity. The prototype achieved an average processing capacity of 96.4 kg/h, with more than 82.5% of the processed material passing through a 4 mm sieve and a dominant fraction of 2–4 mm (54.0%), which is ideal for composting. The specific energy consumption averaged 0.050 kWh/kg, lower than reported values for comparable small-scale biomass shredders. The homogeneity index consistently rated as Good, indicating stable particle size distribution across repeated trials. These findings demonstrate that the developed prototype provides a practical, energy-efficient, and low-cost solution for small-scale organic fertilizer production, supporting sustainable agricultural practices and reducing reliance on chemical fertilizers.
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]

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