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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
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Innovative Emerging Ontology-driven Frameworks: A Systematic Literature Review Mokgetse, Tshepiso Larona; Hlomani, Hlomani; Sigwele, Tshiamo
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v11i4.5106

Abstract

Previous research has shown that ontologies and related semantic web technologies have positioned themselves as good solutions for data integration and resource reusability. Pitfalls and traps in modelling domains can be avoided if researchers and scholars adopt and use ontology-driven frameworks for their research. This research work aims to review currently developed or proposed ontology-driven frameworks, and clearly illustrate their development, application, and practicality. The review then ultimately addresses three main research questions driving the literature review through a synthesis of information that exists about ontology-driven frameworks. Search strings were used to obtain articles from online electronic databases. The PRISMA chart was used for the final selection of the 60 articles for review. A method of scoring called the Assessment of Multiple System Reviews (AMSTAR) was used on the included studies for quality assessment. The AMSTAR mean overall result was 9, the median 10, and the standard deviation 0.99.  The results reveal a downward trend of ontologies in 2010, with Web Ontology Language (OWL) being the most used language for ontology-driven frameworks and systems, with over 70% usage.
The Impact of Semantic Web and Ontology to Improve E-government Services: A Systematic Review Altahir, Badraldeen Hassan; Karrar, Abdelrahman Elsharif; Mohmmed, Shazali Siddig
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.5024

Abstract

The semantic web and ontology are extensions of the World Wide Web that aim to make data more interconnected and machine-readable.  This systematic review examined researched publications published between 2018 and 2023 and indexed in Google Scholar and Science Direct.  23 records were chosen and classified into six groups: information and retrieval, knowledge archiving, interoperability, enhancing public and employee services, barriers to ontology application, and use of ontologies to apply the regulations.  This study explored the semantic web and ontology used to enhance e-government services.  It found that improving ontology for searched and information retrieval processes could help computers retrieve accurate results, improve interoperability and integration, and provide a knowledge base for terms used in building databases and applications. However, more research is needed to effectively integrate ontology into existing systems and extend these approaches to real-world contexts.   Future research should focus on presenting an applied model of e-government technology and conducting continuous evaluations.
Efficient Dual Mode Arbitration Scheme for Multiprocessor Hardware Interface in System-on-Chip Motakabber, S. M. A.; Rokon, Mohammed Iqbalur Rahman; Alam, AHM Zahirul; Matin, Mohammad A; Mahmud, Md
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.5032

Abstract

A processor transforms human needs into hardware operations in any SoC. The single processor was ubiquitous in previous systems. But as chip size, complexity, and speed increase, several processors are used nowadays to handle concurrent operations. To manage requests from several processors, a central hardware block will conduct the arbitration among the processors and allow a processor to access the bus. This paper addresses the multiprocessor arbitration in any System on Chip or ASIC. There are several arbitration algorithms  available in the realm of technology, and any system can choose a specific arbitration to implement in hardware based on its own demands. Instead of using one type of arbitration in hardware, this research combined and used two schemes and implemented both possibilities in a hardware dual-mode arbiter system to be used in SoC. The proposed dual-mode arbiter was initially hardware modeled using Verilog HDL, then functionalities were verified using industry simulator Cadence and Modelsim, and finally synthesized and implemented using Xilinx XST EDA tool and FPGA device.   The AMBA, the industry-standard bus protocol, is being considered for the master processors and the proposed dual-mode arbiter to ensure an efficient hardware interface and to use with any off-the-shelf macro available for the high-tech industry.
Compact Dual-Frequency Slot Antenna for C-Band Applications Based on Substrate Integrate Waveguide Keriee, Hussam; Essa, Eman Hassan; Mahdi, Haider S.; Nayyef, Nawres Abbas
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.4841

Abstract

This paper provides a compact substrate-integrated waveguide-based dual-frequency H-fractal slot antenna for the C-band (SIW). From the view of fractal slot antenna, two H-fractal slot shaped elements with 3rd iteration are used to cut currents in two TE modes, which leads to dual-frequency performance and reduces the size. The antenna operating at dual frequency of 4 GHz and 5.7 GHz with gain greater than 5 dB is designed and fabricated. Measured and simulated response of the antenna are introduced as well. The responses showed that the proposed antenna achieved stable dual-frequency performance with total size of 23 × 11 mm², which may be applied for C-band communication systems. The proposed antenna was simulated, analysed, and optimized using computer simulation technology (CST) software.
Impact of Trust on The Willingness to Use E-Government Services Assegaff, Setiawan; Aryani, Lies; Sunoto, Akwan; Usmayanti, Vivi
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.5200

Abstract

The primary objective of this study was to gain insight into individual perceptions of using online public services offered by local governments. The research aimed to determine how performance expectancy, effort expectancy, trust in government, facilitating conditions, and social influence impact individuals' intentions and behaviors in using online government services. Data were collected using an online questionnaire, and analysis was conducted using structural equation modeling with SmartPLS. The key findings include the positive influences of trust in government and facilitating conditions on users' intentions and behaviors related to e-government services. However, the study did not identify a significant relationship between performance expectancy, effort expectancy, and social influence concerning user intentions and behaviors in using e-government services.
Personal Assistant Development by CED (Canine Eye-disease Detection) Chun, Kyunghan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.5177

Abstract

In this paper, we develop a deep learning-based canine eye disease detection and utilize it to create a dog health management system. With the recent surge in the number of pet dogs, ensuring their well-being has become crucial. We achieve this by applying lightweight deep learning methods like MobileNet and SqueezeNet to mobile devices, enabling regular monitoring of a pet's eye health. Additionally, we provide a GPS-based search feature for nearby hospitals, facilitating swift response to diseases. The validity of the developed method is demonstrated through experiments on 5 eye diseases. The results confirm the importance of considering appropriate recognition rates and recognizability metrics, as outcomes may vary depending on the applied deep learning approach.
Neurorehabilitation Robot-Assisted for Stroke Recovery: Hybrid Exoskeleton Assistive Limb (HEAL) Xue, Law Cheng; Mohd Noor, Anas; Zakaria, Zulkarnay; Mohd Nasir, Nashrul Fazli; Nasrul Norali, Ahmad; Nukman Khiruddin, Khalis Danial
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 4: December 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i4.5166

Abstract

Conventional rehabilitation techniques that require manual intervention and the use of devices are identified as having several drawbacks. These include limited features, fatigue for both patients and therapists during prolonged rehabilitation sessions, time-consuming procedures, high operational and maintenance costs for devices, a lack of motivation for patients, limited accessibility, and challenges in measuring or monitoring rehabilitation progress. In response to these challenges, the Hybrid Exoskeleton Assistive Limb (HEAL) is introduced as a tailored solution with distinctive features. These features include real-time electromyographic (EMG) monitoring, a therapist-friendly graphical interface, and advanced techniques in the rehabilitation process. HEAL utilizes robotics-assisted rehabilitation for repetitive, precise, and controlled movements, enhancing brain-muscle motor function, developing muscle strength, and providing a wide range of motion. The system focuses on upper limb robotic rehabilitation and consists of an EMG to read muscle responses, an Arduino microcontroller for signal processing, and a high-torque precision servo motor for controlling limb movements. HEAL emphasizes the Brain-Muscle-Computer control process rather than passive rehabilitation, which relies on external forces to move the muscles, as demonstrated by the therapist. HEAL is particularly suitable for neurorehabilitation, emphasizing recovery and improvement of function in individuals with neurological disorders or injuries, especially in stroke patients. HEAL's ability to tailor rehabilitation programs individually offers personalized rehabilitation, considering each patient's unique needs, goals, and abilities. It utilizes advanced technologies for targeted and efficient rehabilitation. The HEAL device is cost-saving with a compact design, positioning it as a promising and comprehensive solution in stroke neurorehabilitation.
Diagnosis and Monitoring Method for Detecting and Localizing Bearing Faults Dahmane, Saida; Berrabah, Fouad; Defdaf, Mabrouk; Salah, Saad
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.4612

Abstract

Induction motors in modern industry are becoming more and more functional and complex. Unfortunately, these machines are not free from damages what make their fault diagnosis the most critical aspect of system monitoring and maintenance. Vibrational signal data yields relevant information about the state of the entire system, as well as specifically about one of its components that makes its analysis quite interesting. For this effect, the current paper aims to propose an automatic diagnosis and monitoring method for detecting and locating bearing faults in an induction motor based on vibration signal processing. The suggested method combines the discrete wavelet transform (DWT) with the envelope spectrum (ENV) as advanced signal processing, incorporating a machine learning algorithm based on random forest classifier. The discrete wavelet transforms (DWT), using the Haar wavelet, decomposes the vibrational signal to provide both approximations and details. Each detail is then reconstructed to avoid any missing of information. To precisely select the reconstructed detail (?????) that provides pertinent information about bearing faults, a statistical study is conducted. This study involves calculating four indicators (Root mean square (RMS), correlation coefficient (CC), energy coefficient (EC) and peak to peak (P2P) factor) is performed for each (?????). These indicators are compared with threshold indicators, and this criterion is met by the reconstructed details 1 and 3. The obtained reconstructed details are then subjected to the spectral envelope analysis to detect the fault frequencies, which are considered as new features entering the random forest classifier model. This combination of approaches allows better feature extraction and structuring of the dataset, leading to improved accuracy of the random forest classifier, achieving a higher classification rate of more than 99,53 %. The proposed DWT-ENV-RF method indicates well its efficiency when compared to other recent works, and the attained results are all confirmed by the experimental tests conducted in the CWRU laboratory.
An Exhaustive Survey on Authentication Classes in the IoT Environments Dargaoui, Souhayla; Azrour, Mourade; El Allaoui, Ahmad; Guezzaz, Azidine; Alabdulatif, Abdulatif; Alnajim, Abdullah
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i1.5170

Abstract

In today's world, devices are interconnected across various fields, ranging from intelligent buildings and smart cities to Industry 4.0 and smart healthcare. IoT security is still the biggest obstacle to deployment despite the exponential growth of IoT usage in our world. The principal objective of IoT security is to warrant the accessibility of services offered by an IoT environment, protect privacy, and confidentiality, and ensure the safety of IoT users, infrastructures, data, and devices. Authentication has become a top priority for everyone because it is the first line of defense against security threats and can allow or prevent users from accessing resources according to their legitimacy. Consequently, studying and researching authentication issues within IoT is extremely important. Our paper provides a comparative study of current IoT security research; it analyzes recent authentication protocols from 2018 to 2024. This survey’s goal is to provide an IoT security research summary, the biggest susceptibilities, and attacks, the appropriate technologies, and the most used simulators.
A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array with Undefined Mutual Coupling Famoriji, Oluwole John; Shongwe, Thokozani
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 1: March 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v12i1.4531

Abstract

In antenna array signal processing, estimating the direction-of-arrival (DoA) remains a challenge and basic problem. In this paper, a DoA estimation technique using support vector machine (SVM) classification is developed using spherical antenna array (SAA). The source signal impinging on SAA is decomposed using spherical harmonics (SH). Both magnitude and phase features are computed from the decomposed SH signals. The magnitude and phase features are classified into DoA classes using multi-class SVM (MC-SVM) algorithm. Due to the deterministic and non-probabilistic nature of SVM algorithm, it exhibits high computational speed and less complex than the neural network-dependent learning algorithms. Numerical experiments and experimental measured data (generally accepted ground to test any method) are used to evaluate the performance of the proposed technique. The developed algorithm exhibit high level of robustness at different signal-to-noise ratios (SNR) in the estimation of DoA. Root mean square error (RMSE) performance metrics is employed in the analysis of the proposed method against the state-of-the-art. The results obtained are motivating enough for the deployment of the proposed algorithm in practical scenarios.

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