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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 9,138 Documents
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Short-term recall comparison of iconic auditory and visual feedback stimuli in a memory game Wersényi, György; Csapó, Ádám; Tóllár, József
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp310-321

Abstract

Multimedia user interfaces incorporate various feedback methods using different modalities. Cognitive processing of audiovisual information requires the ability to recall visual and auditory information, either separately, or in combination. Short-term memory capabilities vary individually and depend on factors such as signal presentation and the number and type of visual and auditory items. In an experiment involving 40 subjects, we aimed to compare short-term auditory and visual capabilities in a serious game application. Subjects played the ‘Pairs’ game at different resolutions, using either visual icons or audio samples, while the total time cost and number of flips were recorded. The results indicate that visual memory is not superior, and female subjects performed better than males at higher levels in the visual task. Additionally, human sound samples, speech and familiar auditory icons were found to be easier to recall than artificial measurement signals.
Renewable energy conversion systems for global emission neutralization Suwarno, Suwarno; Cahyadi, Catra Indra; Manurung, Pardamean; Rahim, Abdul; Tanjung, Farhan; Birje, Herman; Syafni, Fadly; Kurnia, Muhammad Ridho; Faruqi, Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp79-88

Abstract

Fossil fuel power plants still play an essential role in providing energy worldwide, but their environmental impact will contribute significantly to emissions and environmental pollution. To reduce these emissions, renewable energy offers a solution to reduce global emissions. This study proposes a renewable energy modeling system using hybrid optimization of multiple energy resources (HOMER) simulation on renewable energy systems for economic savings. This simulation can combine photovoltaic (PV), wind power (WP), and converter systems. The hybrid combination of PV and WP is the most appropriate and economical choice at the research location. The results showed that the modeling of the renewable energy hybrid system made a significant contribution, with an initial investment cost of IDR 107,474.43 million and an annual operating cost of IDR 22,540.23 million, 41% lower on condition now with an estimated return on investment of 11 years. The results of this study can be used as recommendations for similar conditions in other places. Policymakers can use this model to provide incentives and have a positive impact on hybrid power plants (HPS) in neutralizing global emissions.
The impact of COVID-19 on e-commerce: a cross-national analysis of policy implications Cheong, Jia Qi; Tsen, Wong Hock; Abdul Karim, Samsul Ariffin; Cheah, Jeffrey S. S.
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1946-1956

Abstract

The field of e-commerce research has evolved over recent decades, but the coronavirus disease 2019 (COVID-19) pandemic significantly accelerated its prominence, as evidenced by extensive literature. The pandemic underscored the pivotal role of e-commerce in driving the digital transformation of the global economy. However, there remains a lack of comprehensive reviews in this area, particularly comparative analyses of how different countries leveraged e-commerce to navigate the pandemic’s challenges. This paper addresses this gap by examining the literature on e-commerce adoption and its implications during COVID-19, focusing on select countries, including China, Malaysia, and several European nations. The case of China, as a major economic power in Asia, offers particularly valuable insights.
Adaptive mathematical modeling for predicting and analyzing malware Beketova, Gulzhanat; Manapova, Ainur
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1698-1707

Abstract

In this paper, we propose and investigate an improved mathematical model of malware propagation in network structures based on a modification of the well-known raw-immune-response susceptible-infected-recovered (SIR) model. For detailed numerical analysis, our study introduces the fourth-order Runge-Kutta method, which provides higher accuracy in determining fundamental parameters such as infection, recovery and immunity loss coefficients of network nodes. The obtained simulation results demonstrate that the peak of the epidemic occurs when 34.7% of all nodes are infected, with a peak after 32.5-time units. The main contribution of this work is the in-depth understanding and quantification of cyber threats, which emphasizes the importance of prompt response, regular system software updates, and continuous monitoring of network activity. This research makes a significant contribution to cybersecurity applications by providing quantitative tools and strategies to help strengthen network defenses against malicious attacks. The identified patterns and their numerical interpretation can be integrated into processes for optimizing measures to prevent the widespread spread of malware, thereby enhancing the overall security and stability of networked systems.
Study on neuromorphic computation and its applications Chature, Anjali; Raganna, A.; Venkateshappa, Venkateshappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp272-282

Abstract

Neuromorphic computing offers a promising alternative to traditional von Neumann architectures, especially for applications that require efficient processing in edge environments. The challenge lies in optimizing spiking neural networks (SNNs) for these environments to achieve high computational efficiency, particularly in event-driven applications. This paper investigates the integration of advanced simulation tools, such as Simeuro and SuperNeuro, to enhance SNN performance on edge devices. Through comprehensive studies of various SNN models, a novel SNN design with optimized hardware components is proposed, focusing on energy and communication efficiency. The results demonstrate significant improvements in computational efficiency and performance, validating the potential of neuromorphic architectures for executing event-driven scientific applications. The findings suggest that neuromorphic computing can transform the way edge devices handle event-driven tasks, offering a pathway for future innovations in diverse application domains.
Effective methods for employee performance assessment Himawan, Agatha Beny; Kridalukmana, Rinta; Prahasto, Toni
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp509-522

Abstract

This study aims to select the most effective multi-criteria decision-making method used in an employee performance appraisal system. The approach used in this study is a comparative experiment where three multi-criteria decision-making methods simple additive weighting (SAW), analytical hierarchy process (AHP), and technique for order preference similarity to an ideal solution (TOPSIS) are compared. The dataset involves 16 employees, considering input data such as work behavior scores, and performance targets (SKP). The criteria for evaluating work behavior include service quality, accountability, competence, harmony, loyalty, adaptability, collaboration, and achievement of targets. The comparison results were tested using a one-way ANOVA to evaluate whether there are significant differences among the three methods, as well as to provide supporting evidence for the conducted research. The results indicated that the SAW method provides the most accurate and relevant performance assessments while AHP yields less precise rankings as some employees received the same scores despite having different workloads. TOPSIS also produced rankings that did not accurately reflect the relative workloads. Implementing the SAW method in the employee performance information system enhances the assessment process, making it faster, more objective, transparent, and credible. Thus, SAW emerges as the most effective method for aligning performance scores with employee roles and responsibilities.
For S-band WLAN applications, a patch antenna design, simulation, and optimization Ahmed, Md. Eftiar; Pranto, Biprojitt Saha; Rana, Md. Sohel; Faruq Shakil, Md. Omar; Ala Walid, Md. Abul; Arin, Ifat; Mondal, Saikat; Chooyan, Samanta Mostafa
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1613-1623

Abstract

A rectangular microstrip patch antenna for 2.45 GHz is designed, tested, and analyzed in this study. It uses two substrate materials (design I and II) with different permittivity levels. RT5880 (design-I) and FR-4 (design-II) substrates have a thickness of 1.57 mm and 1.6 mm, respectively. Design-I and design-II substrates have relative permittivity of 2.2 and 4.3, respectively. Performance and efficiency are considered due to the substrate material's relative permittivity and thickness; return loss (S11), voltage standing wave ratio (VSWR), gain, directivity, surface current, and efficiency. Design II and design I have 3.25 dBi and 8.089 dBi gains, respectively, and 5.92 dBi and 8.64 dBi directivity, respectively. Design I had the best antenna efficiency, 93.64%, compared to design II, 54.96%. In contrast to the design I and design II, which had return losses (S11) of -53.29 dB and -51.38 dB, each of the suggested antennas had a return loss (S11) of more than -50 dB. The VSWR for design I is 1.0043, while the Design II material is 1.0054. This study aims to reduce return loss (S11) and close the VSWR to 1. This proposed design improves antenna gain, directivity, and efficiency for future wireless applications on wireless local area networks (WLANs).
Enhanced deep auto encoder technique for brain tumor classification and detection Badashah, Syed Jahangir; Moholkar, Kavita; Bangare, Sunil L.; Gupta, Gaurav; T., Devi; Francis, Sammy; Hariram, Venkatesan; Omarov, Batyrkhan; Rane, Kantilal Pitambar; Raghuvanshi, Abhishek
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp2031-2040

Abstract

A brain tumor can develop due to uncontrolled proliferation of aberrant cells in brain tissue. Malignant tumor can influence the nearby brain tissues, potentially resulting in the person's death. Early diagnosis of a brain tumor is crucial for ensuring the survival of patients. This article introduces an improved method using a deep auto encoder for the classification and detection of brain tumor. Magnetic resonance imaging (MRI) images are obtained from the BraTS data sets. The images undergo preprocessing using an adaptive Wiener filter. Image preprocessing is essential for eliminating noise from the input MRI pictures, hence enhancing the accuracy of MRI image classification. The fuzzy C-means technique is used to accomplish image segmentation. The classification model comprises deep auto encoder, convolution neural network (CNN), and K-nearest neighbor techniques. The classification model is developed and evaluated using MRI image slices from the BraTS dataset. Accuracy of deep auto encoder is 98.81%. Accuracy of CNN is 95.50 and accuracy of K-nearest neighbor (KNN) technique is 91.30%.
Autonomous driving system and system hacking protection using V2X communication Rhee, Eugene; Cho, Junhee
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp131-138

Abstract

In this paper, a new autonomous driving system is proposed and problems such as systematic errors that may occur in the autonomous driving system were solved through vehicle to everything (V2X) communication technology. In the actual driving environment, accidents caused by the absence of communication between drivers and communication with infrastructure are frequently exposed. To solve these problems, a system was established that linked V2X communication with a vehicle system. In order to predict and study how this technology works in real traffic situations, it requires a lot of time, manpower, and funds because it requires building an environment similar to real traffic situations and using measuring equipment. For this reason, the system was built with simple model, and the research was conducted through simple simulation. In addition, as network technology and sensing technology for autonomous vehicles develop, the risk of hacking is also increasing. In this paper, various expected attack paths and methods that can hack autonomous vehicles are explained, and methods for defending them are presented.
Banking security and performance of islamic banks in middle east: the role of regulatory quality Almomani, Mohammed Abd-Akarim; Al-Momani, Adai
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp691-699

Abstract

Transaction security is critical for the reputation and trust of banks. Few studies examined how transaction security can impact the financial performance of Islamic banks in developing countries with mixed results emerging in the literature. The research examines how transaction security affects bank financial performance. Three indicators are used to measure the financial performance and includes return on assets (ROA), return on equity (ROE), and Tobin’s Q. Regulatory quality are proposed as a moderating variable. Data was collected from 59 banks in MENA between 2015 and 2022. The results showed that transaction security affected positively ROE and Tobin’s Q. However, there is no significant effect on ROA. Regulatory quality moderated only the effect of transaction security on ROE and Tobin’s Q. Enhance the transaction security and improving the regulatory quality will enhance the financial performance of banks in MENA.

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