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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
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Articles 61 Documents
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Search results for , issue "Vol 39, No 2: August 2025" : 61 Documents clear
Ethics in human-robot interaction research Moreno, Robinson Jimenez; Espitia Cubillos, Anny Astrid; Martinez Baquero, Javier Eduardo
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1005-1012

Abstract

This paper explores the basic ethical and bioethical considerations necessary to mediate interaction with various everyday robots, analyzing several stateof-the-art reports and own research, considering advances in human-robot interaction (HRI) and artificial intelligence (AI). It is important to indicate that the adoption of robotic assistance systems is limited by users' nervousness about the enforcement of ethics, security and privacy of their information, in addition to the regular threats of Internet use, considering that HRI must reason its social and ethical impacts by including specific issues associated with HRI such as autonomy, transparency, deception and policies. In this way, it is relevant both to evaluate how robotic architectures influence people's daily lives and to study how to avoid possible negative impacts. Finally, it is significant to establish the ethical considerations required to enable the development of AI algorithms that help HRI in a natural way.
Technology in halal certification: a ten-year bibliometric study Timur, Yan Putra; Suryaningsih, Sri Abidah; Canggih, Clarashinta; Nurafini, Fira; Badrul Munir, Maryam Bte; Ali, Asiah Binti
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1280-1298

Abstract

This study explores the role of technology in halal certification using bibliometric analysis. Based on 88 articles from the Scopus database (2014–2024), the research employs tools like Publish or Perish (PoP), Microsoft Excel, and VOSviewer to reveal the intellectual framework of relevant literature. The finding indicates a steady increase in manuscript productivity from 2014-2024 despite a declining citation trend. Journal of Islamic Marketing, Mohd Zabiedy Mohd Sulaiman, Malaysia, and the National Defence of Malaysia emerged as most prolific journal, author, country, and institution that produce the most, respectively, in publishing on the topic. The paper that has influenced other research the most is Rejeb et al.’s integrating the IoT in the halal food supply chain: a systematic literature review and research agenda. Five significant keyword clusters that frequently show up in the 88 articles examined in this study are halal supply chain, consumer behavior towards halal foods, the role of blockchain in the halal industry, the role of information technology in halal cosmetics, and halal logo in food products. This study highlights the increasing integration of technology in halal certification, emphasizing the need for continuous innovation, interdisciplinary collaboration, and alignment with industry demands to maintain relevance. Additionally, it underscores Malaysia’s leadership in this field while noting the global expansion of halal research, the impact of emerging technologies like blockchain and IoT, and the need for stronger institutional collaboration to enhance transparency, traceability, and market growth.
Efficient object detection for augmented reality based english learning with YOLOv8 optimization Putra, Arya Krisna; Tambunan, Fiqri Ramadhan; Ndruru, Samson; Chowanda, Andry
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1189-1197

Abstract

This study develops a mobile-based augmented reality (AR) application with machine learning for elementary school students to enhance basic English vocabulary learning. The application integrates an optimized YOLOv8 object detection model, designed to recognize 20 common classroom objects in real-time. The model optimization involves replacing standard Conv layers with GhostConv and the C2f block with the C2fCIB block that has significantly improved computational efficiency. Evaluation results show the optimized model reduces the parameters by 22.003% and decreases the file size from 6.2 MB to 4.9 MB. The model performance improved by achieving precision of 83.7%, recall of 73.5% and a mean Average Precision (mAP) of 81.4%. The model was integrated into the Unity platform via the Barracuda library, enabling real-time detection and interactive display of 3D objects. This aplication also complete with English text, translations, example sentences also audio pronunciation. 3D objects representing classroom vocabulary were specifically created to support AR-based learning. Performance testing on a Samsung A14 showed an improved frame rate of 6–12 FPS compared to the original model’s 5–10 FPS. These results demonstrate that the optimized YOLO model effectively integrates with AR technology, creating a more interactive and enjoyable vocabulary learning experience.
Performance evaluation of a photovoltaic system with phase change material in Guwahati Roy, Pallavi; Talukdar, Bani Kanta
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp737-746

Abstract

Recently, there has been a lot of interest in solar photovoltaic (PV) technology as a clean and renewable energy source. The operating temperature of PV modules significantly impacts their performance; as the temperature rises, the modules perform worse. The phase change material (PCM) paraffin wax has been used to cool a PV system passively. The experiment was carried out during summer over three months, viz. April, May, and June when relative humidity was around 80.75% to 86.5% with two identical 20-watt PV panels in Guwahati, India (26.1332° North and 91.6214° East). One panel was coated with PCM, while the other panel functioned as a point of reference. The study reveals an impressive result: the output power produced by the system with PCM was 9.8%, 13.1%, and 10.3% greater than the reference PV, while the surface temperature had been lowered by 21.6%, 26.2%, and 30.6% in the three respective months. High humidity delays the release of latent heat of paraffin wax and hence improves its thermal conductivity. This study adds to the continuing efforts to promote sustainable energy solutions and creates new opportunities to enhance the performance of PV systems.
Enhancing the effectiveness of CAPTCHA using an improved visual cryptography scheme Hasnae, Chihi; Asaad, Chahboun
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1121-1129

Abstract

Traditional CAPTCHA systems, designed to distinguish humans from bots, are increasingly ineffective due to advancements in artificial intelligence (AI), particularly deep learning and optical character recognition (OCR) technologies, which enable bots to bypass these systems. This paper proposes a new CAPTCHA authentication method that combines enhanced visual cryptography with traditional techniques to improve security. Visual cryptography divides information into visually distinct shares, reinforcing CAPTCHA’s defenses against automated attacks, especially those using deep learning. This approach not only strengthens security but also improves user experience by adjusting the time required to complete CAPTCHA challenges, addressing usability concerns associated with traditional systems. Overall, the proposed method offers a more secure, efficient, and user friendly solution for online authentication.
Artificial neural network based load flow analysis of radial distribution system in Kurdistan region Ali, Warda Hussein; Qader, Dana O.; Hussein, Mohamed A.
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp761-773

Abstract

Today electric energy is the most commonly used source in the world. Power flow (load flow) analysis is conciderd as the backbone of any power system analysis and design; they have a great necessity for operating systems, future planning, fault analysis, and contingency analysis. For better utilization of electrical power, off-line modeling and simulation of power systems using powerful software are essential and significant task especially in developing countries and regions. Therefore, this paper performs a comparison study of conventional and non-conventional load flow techniques for a 24-Bus radial distribution system in the governorate of Sulaymaniyah. The conventional power flow techniques include the Newton-Raphson (NR), and Gauss-Seidel (GS) techniques, while the nonconventional load flow technique utilizes the artificial neural network (ANN). Modeling, simulation, and analysis of the 24-Bus feeder are performed using MATPOWER simulation tool. The MATPOWER and neural network techniques are implemented independently, and it has been proved that ANN model efficiently estimated the power flow analysis for the system mentioned above, the high regression values of nearly 0.999 indicates that the ANN model can be used as an efficient tool to perform power flow analysis.
Impact of multipath delay and co-channel interference on MIMO and STBC-MIMO Bongale, Ujwala; Patil, Vinayak; Sable, Ganesh
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp941-951

Abstract

This paper presents a comparative analysis of conventional multiple-input multiple-output (MIMO) systems and space-time block coding (STBC) enhanced MIMO systems across three distinct wireless channel scenarios: flat Rayleigh fading, multipath delay, and multipath delay with co-channel interference. The ability of STBC to exploit multiple independent signal paths between the transmitter and receiver reduces the likelihood of signal fading, which is tried to represent through this work. Using MATLAB simulations, we evaluate system performance under realistic channel conditions, focusing on the key metric of bit error rate (BER). Results show that STBC significantly improves reliability and reduces BER compared to conventional MIMO, particularly under multipath and interference-laden environments.
A curvilinear-based approach for sign-to-text conversion of Kannada deaf sign language Gollagi, Shantappa G; Laddi, Mahantesh; G K, Suhas; Bamane, Kalyan Devappa; Yadav, Sulbha
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1337-1349

Abstract

This research addresses the challenge of translating Kannada sign language into text to improve communication for the deaf community. Existing methods, primarily shape-based approaches, often fail to accurately imprisonment the complexity of hand gestures, leading to reduced translation accuracy. This study proposes a curvilinear-based approach that leverages peak curvature features and contour evolution techniques to overcome these limitations. This method enhances the recognition and interpretation of sign language gestures while reducing processing overhead. Experimental results demonstrate that the proposed system significantly outperforms traditional methods, achieving higher precision and recall rates. The enhanced system provides a reliable solution for improving accessibility and communication for the deaf community. This research represents a significant step toward developing more inclusive digital communication tools, with future work focused on real-time processing and extending the system to other regional sign languages.
Improved counterplan for interference in same-band information transmission and reception Rhee, Eugene; Cho, Junhee
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp831-839

Abstract

Wireless communication technologies operating in the 2.4 GHz band, such as Wi-Fi, Bluetooth, ZigBee, and others, often face challenges related to mutual interference. These technologies share the same unlicensed frequency spectrum, which can lead to various types of interference, affecting performance, reliability, and data throughput. This paper addresses the issue of mutual interference in communications occurring within frequency bands commonly used in daily life. Through this, it conducts an in-depth study on information processing between wireless devices and the control of communication components. Specifically, it examines interference phenomena in the widely used 2.4 GHz band by analyzing communication methods where such interference is likely to occur. By investigating the characteristics of Wi-Fi, Bluetooth, and ZigBee, this study analyzes interference phenomena and proposes an algorithm to mitigate them. To mitigate this, this paper proposes a multi-layered method integrating adaptive filtering, dynamic frequency allocation, advanced error correction, and intelligent scheduling mechanisms.
Enhancing acoustic environment classification for hearingimpaired individuals using hybrid CNN and RFE Hattaraki, Sunilkumar M.; Kambalimath, Shankarayya G.
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp906-913

Abstract

Individuals who are deaf or hard of hearing experience considerable difficulties in distinguishing sounds in various acoustic environments, which affects their communication ability and overall quality of life. Existing auditory assistive technologies currently face challenges with real-time classification and adaptation to changing noise conditions, underscoring the need for more reliable and accurate classification models. This research bridges the existing gap by creating a hybrid classification framework that integrates convolutional neural networks (CNN) and random forest ensemble (RFE) to enhance the accuracy of environmental sound classification. The study utilizes Mel-frequency cepstral coefficients (MFCCs) for feature extraction and principal component analysis (PCA) for dimensionality reduction, thus facilitating the efficient processing of real-world audio data. The proposed methodology improves classification accuracy across various environmental conditions. Experimental evaluations demonstrate superior performance, achieving a training accuracy of 94.93% and a testing accuracy of 93.41%, thereby exceeding conventional machine learning methods. By overcoming limitations in existing models, this research contributes to the development of adaptive hearing assistance systems with enhanced noise classification capabilities. The results have significant implications for the development of smart hearing aids, real-time noise classification, and auditory scene analysis. Ultimately, this research enhances assistive hearing technologies, promoting greater accessibility, communication, and inclusion for hearing-impaired individuals, thus contributing positively to society.

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