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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 :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 36, No 1: October 2024" : 64 Documents clear
MetaLung: Meticulous affine-transformation-based lung cancer augmentation method Nam, Diana; Panina, Alexandra; Pak, Alexandr; Hajiyev, Fuad
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp401-413

Abstract

The limitation of medical image data in open source is a big challenge for medical image processing. Medical data is closed because of confidential and ethical issues, also manual labeling of medical data is an expensive process. We propose a new augmentation method named MetaLung (Meticulous affine-transformation-based lung cancer augmentation method) for lung CT image augmentation. The key feature of the proposed method is the ability to expand the training dataset while preserving clinical and instrumental features. MetaLung shows a stable increase in image segmentation quality for three CNN-based models with different computational complexity (U-Net, DeepLabV3, and MaskRCNN). Also, the method allows in reduce the number of False Positive predictions.
An optimal machine learning-based algorithm for detecting phishing attacks using URL information Devaraj, Nandeesha Hallimysore; Thimappa, Prasanna Bantiganahalli
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp631-638

Abstract

In recent years, more websites have been collecting personal information for many processes, such as banks, internet connections, and government services. The public needs to provide all personal information, such as Aadhar, PAN, date of birth, and phone number. The personal and sensitive information is at risk of being used for phishing attacks through URL manipulation. In addition, a phishing attack cause’s financial and reputational loss. Hence protecting sensitive information by adapting required protection is extremely valuable for global security. To overcome this, we proposed a method to detect phishing attacks based on previous history, including the duration of operation, customer reviews, web traffic, and the URL. Based on these parameters, the proposed optimal machine learning-based algorithm (OmLA) analyze the previous information about URLs and predict whether it is phishing- or legitimate. As per simulation and performance analysis, the proposed method outperforms conventional methods such as random forest (RF), support vector machine (SVM), and genetic algorithms (GA) by 8%, 18%, and 23%, respectively in terms of accuracy. Additionally, it achieves detection times of 0.2%, 0.6%, and 0.9%, respectively, and excels in response times of 0.45%, 0.56%, and 0.62%, respectively.
Improving magnetic fields in overhead transmission lines using the insulated cross-arm method Ahsan, Matiullah; Baharom, Md Nor Ramdon; Zainal, Zainab; Sahari, Norain; Hanim, Faridah; Kamarudin, Saufi; Abd Rahman, Rashisham; Mohd Yousof, Mohd Fairouz; Jamail, Nor Akmal; Othman, Nordiana Azlin
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp53-63

Abstract

This research study evaluates the effectiveness of the insulated cross-arm (ICA) method in reducing magnetic field (MF) levels in transmission lines. Using Ansys Maxwell finite element method (FEM) software, the study models and analyses the MF distribution in 132 kV and 275 kV overhead transmission lines (OTLs) in Malaysia. The findings reveal that implementing the ICA method can substantially reduce MF levels, improving MF performance by 36% (at 132 kV) and 48% (at 275 kV). These findings have important implications for mitigating potential health risks associated with high MF exposure near transmission lines. Furthermore, the study highlights the potential for future enhancements in ampacity and emphasizes the importance of promoting a health-conscious environment. Field studies, assessments, and investigations into economic feasibility and practical implementation are recommended for further validation and application of the ICA method. Overall, this research study contributes to the knowledge and understanding of reducing MF exposure and improving the efficiency of power transmission systems.
Optimizing channel capacity for B5G with deep learning approaches in MISO-NOMA-HBF and BFNN Masud, Muhammad Atique; Al Amin, Ahmed; Islam, Md. Shoriful; Mostafa, Vaskor; Wahiduzzaman, Md.
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp205-213

Abstract

This study proposes the integration of a beamforming neural network (BFNN) and multiple-input single-output based non-orthogonal multiple access (MISO-NOMA) with hybrid beamforming (HBF) for cell edge users (CEU) in a millimeter wave (mmWave)-based beyond 5G cellular communication system. This system is referred to as MISO-NOMA-HBF-BFNN. The proposed scheme has been implemented to support multiple users simultaneously and also to considerably enhance and significantly improve the overall the sum channel capacity (SC) and user channel capacities. Additionally, the simulation results demonstrate the superiority of the proposed MISO-NOMA-HBF-BFNN scheme over the existing MISO-NOMA with HBF and MISO-OMA with HBFBFNN based schemes in terms of user capacities and SC.
A novel AI-AVO approach for maximum power generation of PMSG S. Chinamalli, Prashant Kumar; Sasikala, Mungamuri
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp99-114

Abstract

Permanent magnet synchronous generators (PMSGs) are necessary for producing wind energy that is both highly reliable and reasonably priced. An inventive control technique for the driven interior PMSG (IPMSG) is presented here to maximize wind energy output and decrease losses. This research established an innovative optimization strategy for the highest wind power generation with reduced overall loss in PMSG-based Wind power generation systems. Considering, that the tip speed ratio (TPR), rotor speed ???????? , and quadrature axis current ???????? are optimized in the proposed work in such a way to enhance wind power generation. Further, the direct axis current ???????? is calculated from the optimized rotor speed ????????. The minimization of core loss is considered as the fitness function, which is a function of the direct current axis ????????and quadrature current axis ????????. The optimization is carried out using the explored aquila with African vulture optimization (EA-AVO) technique, which is the conceptual incorporation of prevailing techniques, like the aquila optimization algorithm (AOA) and the AVO algorithm. The performance of the proposed method is validated over the conventional methods, in terms of power output, losses, efficiency, and convergence analysis. According, the findings show that the proposed method attains less overall loss of 149.62 at the starting stage of 50 rotor speed, and it was 36.46% higher than AQO, 36.17% higher than AVOA, 36.59% higher than GOA methods 36.42%, and higher than WHO+PI approaches.
Electronic document management systems implementation across industries: systematic analysis Anggraini, Dian; Adi, Kusworo; Suseno, Jatmiko Endro
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp264-273

Abstract

The construction sector’s pivotal role in the global economy faces challenges due to its dynamic nature. Inaccurate documentation impacts project cost management, underscoring the need for effective document management systems (DMS), including electronic document management systems (EDMS). This study conducts a systematic literature review to comprehensively examine EDMS implementation, utilization, and effectiveness across sectors. Analyzing peer-reviewed articles and scholarly sources reveals key themes, trends, and findings, providing insights into successful EDMS adoption and best practices. The review contributes evidence-based insights for practitioners, researchers, and policymakers, addressing gaps in knowledge and advancing understanding of EDMS in modern information management. Additionally, it presents a detailed breakdown of publication distribution across sectors, highlighting significant research areas like companies and businesses, education, and information technology and software. Furthermore, analysis of factors influencing employee behavior, including technical factors, employee’s personal characteristics, organizational factors, and trust, offers valuable insights into workplace dynamics. Overall, the study offers comprehensive insights into EDMS implementation, guiding future research, and organizational strategies.
Cattle weight prediction model using convolutional neural network and artificial neural network Yulianingsih, Yulianingsih; Nurdiati, Sri; Sukoco, Heru; Sumantri, Cece
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp441-449

Abstract

The weight of livestock is a crucial metric for evaluating management efficacy, informing policy decisions, and determining the market value of animals. In certain scenarios, conventional methods such as physical weighing and measurement calculations can prove challenging, including the absence of livestock health records or weighing equipment. This research aims to develop a predictive model for estimating the live weight of cattle through visual assessments and metadata, including age and pixel count, utilizing a combination of convolutional neural network (CNN) and artificial neural network (ANN) methodologies. A total of 223 data were obtained from a local farm before augmentation. The model's predictive capability was successfully demonstrated, with its performance quantified by an average mean absolute percentage error (MAPE) of 10% on test data. This study demonstrates that through the combination of CNN and ANN, as well as optimal parameter tuning, efficient prediction of cattle weight can be achieved.
Comparative study of wind turbine emulator control using an asynchronous motor: IRFOC and DTC Zekraoui, Hana; Ouchbel, Taoufik; El Hafyani, Mohamed Larbi
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp174-187

Abstract

This work is an overview of one of the renewable energy sources, wind power. The high cost of testing wind turbines and analyzing their characteristics in research laboratories prompted us to create the Wind Emulator. In this article, we will proceed with the development of an emulator of a wind turbine conversion chain based on an asynchronous machine. This emulator would be capable of faithfully reproducing the dynamic characteristics of a real wind turbine and of integrating them optimally into a real electrical system so as to be able to study its operation at laboratory level, so our objective is to have an emulator that will provide the characteristics (speed-torque-current) in real time and with realistic conditions. Our development approach is based on the use of two classical control strategies under the MATLAB/Simulink closed-loop environment: direct torque control (DTC) and indirect rotor flux vector control (IRFOC) in dynamic and static regimes. The simulation results presented and discussed in this work enable us to determine the operating limits of our proposed wind emulator, in order to validate the most suitable emulator model. Ultimately, this model will be integrated into an intelligent computing board such as the DSP1104.
The surprising influence of social commerce service quality on purchase intentions mediated by e-commerce Suwarno, Bukky; Dhewanto, Wawan; Belgiawan, Prawira Fajarindra
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp367-374

Abstract

Social commerce has become a recent phenomenon and is poised to grow rapidly in the next few years. To better address customer behavior on social commerce platforms, it is imperative to acquire a comprehensive understanding of social commerce from the perspective of service quality. The objective of this research is to examine the dimensions of social commerce service quality and to reveal the factors influencing purchase intentions among the expanding user population. This study identified seven critical dimensions of social commerce service quality (website design, fulfilment, customer service, communication, contact, credibility, and security) that influence purchase intention. This research adopts a questionnaire survey method to collect data from social commerce users. Using PLS-SEM, the findings from an empirical analysis, conducted with a sample of 411 social commerce users, demonstrate that all measured dimensions significantly impact the intention to purchase. The findings also demonstrate that e-commerce has considerable influence on customer purchase intention as a partial mediator in social commerce. The findings hold significant implications for social commerce enterprises to increase customer attraction by identifying the motivations behind their purchasing decisions.
Culturally inclusive prototyping for higher education institutions: navigating language and gender dynamics Malkawi, Aminah Rezqallah; Abu Bakar, Muhamad Shahbani; Dahlin, Zulkhairi Md
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp622-630

Abstract

This article explores the crucial intersection of cultural inclusivity in designing and developing e-learning prototypes for Higher Education Institutions (HEIs) in developed countries, such as Saudi Arabia (SA), emphasizing language and gender dynamics. It delves into the deliberate design of prototypes that accommodate linguistic diversity and address gender biases prevalent in educational systems. Real-world examples illustrate innovative solutions institutions use to navigate the complexities of language and gender dynamics during the prototype design process. Notably, the prototypes discussed have undergone rigorous evaluation, ensuring they meet technical benchmarks while aligning with the diverse linguistic and gender aspects inherent to developed nations. By synthesizing cultural sensitivity with cutting-edge design, this article encourages educators, developers, and decision-makers to adopt holistic approaches in creating HEI prototypes. Incorporating cultural inclusivity fosters equitable learning environments and positions higher education to be both forward-thinking and deeply rooted in the cultural tapestry it serves.

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