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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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Aspect term extraction from multi-source domain using enhanced latent Dirichlet allocation Dhanal, Radhika Jinendra; Ghorpade, Vijay Ram
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 1: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i1.pp475-484

Abstract

This study presents a comprehensive exploration of sentiment analysis across diverse domains through the introduction of a multi-source domain dataset encompassing hospitals, laptops, restaurants, cell phones, and electronics. Leveraging this extensive dataset, an enhanced latent Dirichlet allocation (E-LDA) model is proposed for topic modeling and aspect extraction, demonstrating superior performance with a remarkable coherence score of 0.5727. Comparative analyses with traditional LDA and other existing models showcase the efficacy of E-LDA in capturing sentiments and specific attributes within different domains. The extracted topics and aspects reveal valuable insights into domain-specific sentiments and aspects, contributing to the advancement of sentiment analysis methodologies. The findings underscore the significance of considering multi-source datasets for a more holistic understanding of sentiment in diverse text corpora.
Characteristics of symmetrical components for high impedance faults in distribution networks with photovoltaic inverters Herris Yamashika; Syafii Syafii
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 2: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i2.pp727-735

Abstract

This work models a photovoltaic (PV) inverter connected to an IEC microgrid system. The purpose of this study was to find the characteristics of symmetrical components before and after a high impedance single phase short-circuit fault. The IEC microgrid system is tailored to the distribution system in Indonesia, where the applied voltage is 20 kV. Only parameters related to the short-circuit study are included in the model. A second-order generalized integrator frequency-locked-loop is utilized to represent the 3-phase PV inverter. The inverter model, previously treated as an ideal current source, and positive sequence current are no longer employed, as they fail to depict the characteristics of symmetric components during a phase-to-ground short-circuit fault. The IEC microgrid system connected to the PV inverter is simulated using ATPDraw-electro magnetic transient program (EMTP). Simulation results reveal that the changes in the symmetric component values of current after a fault experience a very insignificant increase. Meanwhile, the positive sequence voltage values following the short-circuit fault exhibit a negligible decrease. In contrast, the negative sequence and zero sequence voltage components after the short-circuit fault undergo a significant increase.
Restoration of the service and loss minimization in electrical distribution systems Ganney Poorna Chandra Rao; Pallikonda Ravi Babu
Indonesian Journal of Electrical Engineering and Computer Science Vol 32, No 3: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v32.i3.pp1267-1277

Abstract

Restoration of service during faults to healthy zones and the minimization of true or real power losses are the main aspects of the satisfactory operation of an electrical distribution system (EDS). These objectives can be achieved with artificially intelligent optimisation techniques through electrical distribution system reconfiguration. The restoration of service is an important part of ensuring a stable power supply. If there is a fault with the EDS, the damaged zone is separated, and the healthy system is restored without breaching limitations. In the distribution system, ohmic losses are 25-35%. It is essential to reconfigure the system toreduce these losses. In this paper, a hybrid artificial rabbits’optimisation and improved mayfly optimisation (ARO-IMO) technique is adopted for restoration of serviceand loss minimization. The method being suggested will be carried out on an IEEE 4-feeder network for restoration of service and on IEEE 33 and69 radial distribution networks (RDN) for diminution of losses.
Factors driving business intelligence adoption: an extended technology-organization-environment framework Radhakrishnan Subramaniam; Prashobhan Palakeel; Manimuthu Arunmozhi; Manikandan Sridharan; Uthayakumar Marimuthu
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp1893-1903

Abstract

Business intelligence (BI) is a vital component for businesses of all scales, offering actionable insights crucial for timely decision-making. This technology has become integral across diverse enterprises. Recognizing the factors influencing BI adoption is imperative, and this article employs the organization, complexity, knowledge, technology, user perception and experience, economic, environmental, and social (OCKTUEES) framework to identify key aspects. Building upon the TOE framework, it pinpoints significant variables, emphasizing the importance of factors like user perception and experience, technology, social, economical, and environmental. Employing structural equation modelling on primary data yields actionable insights to address BI adoption challenges. Analysis reveals the user perception and experience, technology, social, economic, and environmental as the top factors. However, the organization appears vulnerable, necessitating a mitigation strategy for successful BI adoption. The study predicts insignificant variables requiring mitigation, such as high costs, inadequate resources, organizational size, security and privacy concerns, risk of open-source adoption, and perception of analytics impacting jobs. This research aids those navigating the BI implementation journey.
Comparing machine learning techniques for software requirements risk prediction Yasiel Pérez Vera; Álvaro Fernández Del Carpio
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp508-519

Abstract

Software requirements are the most critical phase focused on documenting, eliciting, and maintaining the stakeholders’ requirements. Risk identification and analysis are preemptive actions designed to anticipate and prepare for potential issues. Usually, this classification of risks is done manually, a practice that the personal judgment of the risk analyst or the project manager might influence. Machine learning (ML) techniques were proposed to predict the risk level in software requirements. The techniques used were logistic regression (LR), multilayer perceptron (MLP) neural network, support vector machine (SVM), decision tree (DT), naive bayes, and random forest (RF). Each model was trained and tested using cross-validation with k-folds, each with its respective parameters, to provide optimal results. Finally, they were compared based on precision, accuracy, and recall metrics. Statistical tests were performed to determine if there were significant differences between the different ML techniques used to classify risks. The results concluded that the DT and RF are the techniques that best predict the risk level in software requirements.
Improved moth search algorithm with mutation operator for numerical optimization problems Ghaleb, Sanaa A. A.; Mohamad, Mumtazimah; Mohammed Ghanem, Waheed Ali Hussein; Alhadi, Arifah Che; Nasser, Abdullah B.; Aldowah, Hanan
Indonesian Journal of Electrical Engineering and Computer Science Vol 35, No 2: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v35.i2.pp1022-1031

Abstract

The moth search algorithm (MSA) is a meta-heuristic optimization technique inspired by moth behavior, has shown remarkable efficacy in solving optimization challenges. However, its poor exploration capability results in an imbalance between exploitation and exploration. To address this issue, this research introduces a new mutation operator to enhance exploration by increasing population diversity. The proposed enhanced moth search algorithm (EMSA) aims to expedite convergence and improve overall robustness by exploring new solutions more effectively. Evaluation on ten benchmark functions demonstrates EMSA's superior exploration capabilities, efficiently tackling optimization problems and yielding more optimal solutions within the search space. Compared to conventional MSA and other established algorithms, EMSA delivers well-balanced results, showcasing its effectiveness in optimizing the search space. In the future, the EMSA could potentially find applications in addressing real-world engineering optimization challenges.
Interface design features and evaluation of batik 4.0 mobile application Nova Suparmanto; Anna Maria Sri Asih; Andi Sudiarso; Paulus Insap Santosa
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 3: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i3.pp1604-1619

Abstract

The use of information and communication technology could increase the quantity and quality of small medium enterprises (SME) production, including batik industry. This study focuses on the development of batik 4.0, a custom batik mobile-based interface that makes it easier for customer which can be used to quickly produce high-quality digital batik designs. The findings of this study simplify the ordering process for potential clients who want to acquire custom batik designs. Ease of transactions, namely down payments (DP) where users can make advance payments, so that users are relieved in terms of payment transactions. In designing mobile devices, applications, and user interfaces (UI), it is important to consider the user experience (UX). This paper focuses on UX design rooted in the user-centered design (UCD) approach, placing emphasis on understanding user requirements and prioritizing empathy for users. This ensures the recognition of user needs and the creation of a high-fidelity prototype. Then it was validated by the UI experts to identify problems and user difficulties in interacting with the UI. The experts responded positively towards the application and suggest for prototype improvement. Lastly, UX testing; based on the user experience questionnaire (UEQ)-S benchmark results, the batik 4.0 mobile is included in the “Excellent” category.
Development of a novel optimization algorithm for a microstrip patch antenna array Fredelino A. Galleto Jr; Aaron Don M. Africa; Ara Jyllian A. Abello; Joaquin Miguel B. Lalusin
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp126-134

Abstract

Microstrip patch antennas are typically used because they have a low profile and cost. The main theme of this study is to present a novel 2×2 microstrip antenna array design using rough set theory. In designing the 2×2 microstrip antenna array, an FR4 dielectric substrate was used to improve the performance. The rough set theory was used to optimize the microstrip antenna parameters. The FR4 dielectric substrate compared better to the microstrip patch antenna array wherein no substrate was used. The antenna with no substrate used had the energy that is radiating underneath which contributed to the sidelobes of the radiation pattern whereas the use of the substrate reduced the energy radiated at the substrate. Furthermore, the gains of the two were also simultaneously evaluated and it showed that the microstrip antenna array with the dielectric substrate had better gain than the one without. This 2×2 microstrip array antenna design may be used for applications such as mobile communications since it is small in size and performs well.
Enhancing EEG-based brain-computer interface systems through efficient machine learning classification techniques Ferdi Ahmed Yassine; Ghazli Abdelkader
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i3.pp2045-2054

Abstract

Advances in the fields of neuroscience and computer science have greatly enhanced the human brain’s ability to communicate and interact with the surrounding environment. In addition, recent steps in machine learning (ML) have increased the use of electroencephalography (EEG)-based BCIs for artificial intelligence (AI) applications. The prevailing challenge in recording EEG sensor data is that the captured signals are mixed with noise, which makes their effective use difficult. Therefore, strengthening the classification stage becomes extremely important and plays a major role in addressing this problem. In this study, we chose five most widely used classification models that obtained the best results in this field and tested them on two open-source databases. We also focused on improving the hyperparameters of each algorithm to obtain best results. Our results indicate excellent results on the first dataset and acceptable for most models on the second, while RF showed superior performance on both with an accuracy of 100% on the first dataset and 86.47% on the second. This was achieved with the lowest training costs, and better performance compared to previous works we evaluated that used the same databases. These results provide valuable insights and advance the development of brain-computer interface (BCI) technology and design.
Discontinuous Arabic frozen expressions modelization and implementation Asmaa Kourtin; Asmaa Amzali; Mohammed Mourchid; Samir Mbarki
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp342-349

Abstract

Frozen expressions hold significant importance in the field of natural language processing, attracting considerable attention from researchers across various languages in recent years. The Arabic language, in particular, boasts a wealth of frozen expressions inherited from the pre-Islamic and early Islamic periods, with persistent usage to the present day. This linguistic richness has motivated researchers to systematically collect, classify, and elucidate these expressions. Various classifications have emerged, addressing aspects such as continuity, discontinuity, allowance for variations, and restriction from variations. Our aim is to produce lexicon-grammar tables of discontinuous Arabic frozen expressions and implement them. Our approach involves the meticulous collection and study of these expressions, followed by the transformation of their lexicon-grammar tables into dictionaries and syntactic grammars within the NooJ platform. This methodology allows us to recognize and annotate these expressions in texts and corpora, even when they exhibit discontinuity. Such recognition has the potential to address several challenges in automatic natural language processing, including the area of automatic translation.

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