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Risanuri Hidayat
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Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada Jl. Grafika No 2. Kampus UGM Yogyakarta 55281
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INDONESIA
Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Published by Universitas Gadjah Mada
ISSN : 23014156     EISSN : 24605719     DOI : 10.22146/jnteti
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, Power Distribution, Power Conversion, Protection Systems, Electrical Material 3. Signals, Systems, and Electronics: Digital Signal Processing Algorithm, Robotic Systems and Image Processing, Biomedical Instrumentation, Microelectronics, Instrumentation and Control 4. Communication Systems: Management and Protocol Network, Telecommunication Systems, Wireless Communications, Optoelectronics, Fuzzy Sensor and Network
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 644 Documents
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Application of You Only Look Once (YOLO) Method for Sign Language Identification Reni Triyaningsih; Pradita Eko Prasetyo Utomo; Benedika Ferdian Hutabarat
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.21931

Abstract

Limited understanding of sign language has widened the social gap for deaf people, creating barriers in communication and social interaction. To address this challenge, technology-based solutions are required to facilitate inclusive communication. Deep learning-based detection methods, particularly the You Only Look Once (YOLO) algorithm, have gained attention for their speed and accuracy in real-time object detection. This research aims to develop and evaluate a YOLO training model for the identification of Indonesian sign language system (sistem isyarat bahasa Indonesia, SIBI). The dataset was obtained from resource person at the State Special School Prof. Dr. Sri Soedewi Masjchun Sofwan, SH. Jambi, and enriched with additional images collected from external subjects. Augmentation techniques with Roboflow were applied to expand the dataset, and several training schemes were implemented. Model performance was assessed using confusion matrix while considering accuracy and indications of overfitting. The results showed that the quality and quantity of training data, as well as the epoch values, strongly influenced the accuracy of the trained model. The best performance was achieved with 40 primary images per label class, augmented to 60 images, and trained over 24 epochs, resulting in a confusion matrix accuracy of 99.9%. The implemented model was able to recognize SIBI gestures in real-time using a webcam with fast processing. Overall, the proposed YOLO-based model successfully identifies sign language in real-time and demonstrates strong potential for reducing communication barriers among deaf people. However, further refinement and expansion of the dataset are recommended to improve effectiveness and enable broader real-world applications.
Sentiment Analysis Review Threads Google Play Store with RoBERTa Model Natan Kharisma A; Lestari, Dewi; Gatot T Pranoto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.22038

Abstract

The rapid development of internet technology globally, including in Indonesia, has drastically changed communication and interaction patterns between individuals. One impact is seen in the increasing use of text-based social media applications, such as Threads, developed by Meta. Within a short time, Threads managed to attract millions of users. However, the large number of user reviews on the Google Play Store presents its own challenges, particularly in manual sentiment analysis, which is very time-consuming and prone to bias. This research aims to overcome these challenges by implementing a variant of bidirectional encoder representations from transformers (BERT), the robustly optimized BERT pretraining approach (RoBERTa) model, which has been optimized for natural language processing. The research process followed the cross-industry standard process for data mining (CRISP-DM) framework, including several main stages: understanding the business context, data exploration and model building preparation, performance evaluation, and model deployment. Data were obtained directly from the Google Play Store and then cleaned through deduplication, normalization, and tokenization stages. The RoBERTa model demonstrated strong performance, with an accuracy of 88%. Precision was recorded at 92% for positive sentiment and 81% for negative sentiment, while recall was at 88% and 87%, respectively. The F1 score was also high, at 90% for positive and 84% for negative sentiment. When compared to algorithms like naïve Bayes and support vector machine (SVM), RoBERTa proved superior. This research opens opportunities for exploring other transformer models or using ensembles to improve performance in the future.
Implementasi PID Auto Tuning Berbasis PLC Omron untuk Pengendalian Kestabilan Kecepatan Motor Induksi Tiga Fasa terhadap Variasi Beban: Sebuah Studi Eksperimenta Rohadi, Nanang; Liu Kin Men; Akik Hidayat
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.22693

Abstract

Speed regulation of three-phase induction motors under varying load conditions presents a major challenge in industrial automation due to their nonlinear dynamic behavior. This paper proposes an adaptive speed control system using a PID Auto-Tuning (PIDAT) algorithm implemented on the Omron CP1H-XA40DT-D Programmable Logic Controller (PLC). The initial PID parameters are derived using the Ziegler–Nichols method, and the system continuously monitors steady-state error during operation. When the error exceeds a predefined 5% threshold, the auto-tuning sequence is triggered. This sequence includes a Relay Feedback Test (RFT), system identification using a First-Order Plus Dead Time (FOPDT) model, and real-time PID parameter recalculation. The system hardware integrates an Omron 3G3MX2 inverter, rotary encoder, and NB7W-TW01B Human–Machine Interface (HMI) to form a closed-loop control structure. Experimental validation was performed under both spontaneous and constant load conditions. The PIDAT method consistently demonstrated superior performance compared to classical Ziegler–Nichols tuning, achieving steady-state errors in no-load tests below 1.70 % and under 0.8% in loaded conditions. Furthermore, the system achieved settling times below 9 seconds and recovered from load disturbances in less than 4 seconds. These results validate the proposed PIDAT system as an accurate, fast, and adaptive control solution, reducing the need for manual tuning and enhancing robustness in dynamic industrial environments.
Virtual Inertia Control Topology Addressing Indonesia’s Low-Inertia Renewable Grid Resilience Challenge F. Danang Wijaya; Fikri Waskito; Eka Firmansyah; Juan C. Vasques
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 14 No 4: November 2025
Publisher : This journal is published by the Department of Electrical and Information Engineering, Faculty of Engineering, Universitas Gadjah Mada.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v14i4.25234

Abstract

The increasing penetration of renewable energy sources in Indonesia, particularly photovoltaic (PV) systems, into electric power grids has led to a reduction in system inertia, potentially compromising frequency stability during disturbances. This paper proposes a virtual inertia control method for single-phase rooftop PV inverters to enhance frequency response in low-inertia microgrids. A single-phase synchronverter model based on the swing equation is developed and tested on the IEEE 13-bus system. Three scenarios are evaluated: a solar-only microgrid, a wind-integrated microgrid, and a microgrid combining renewable sources with a synchronous generator. Simulation results demonstrate that the proposed virtual inertia method improves frequency and voltage stability, closely mimicking the response of traditional synchronous generators. Within the first 10 seconds following a disturbance, the system fails to restore its frequency to the nominal value due to insufficient inertia in the inertial response time range. This indicates that the initial 10 seconds are a critical period for frequency recovery. The poorest frequency response is observed in Scenario 1 (solar-only configuration), where system inertia is the lowest among the three scenarios, while the hybrid configuration with a synchronous generator (Scenario 3) provides the most stable and robust frequency performance. The findings support the recommendation to implement policies requiring rooftop PV systems to incorporate virtual inertia functionalities, ensuring greater system resilience as renewable energy penetration increases.

Page 65 of 65 | Total Record : 644

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