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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 66 Documents
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Search results for , issue "Vol 34, No 2: May 2024" : 66 Documents clear
Web mining and sentiment analysis of COVID-19 discourse in online forum communities Masurah Mohamad; Suraya Masrom; Khairulliza Ahmad Salleh; Lathifah Alfat; Muhammad Nasucha; Nur Uddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1280-1287

Abstract

Recently, various discussions, solutions, data, and methods related to coronavirus disease 2019 (COVID-19) have been posted in online forum communities. Although a vast amount of posting on COVID-19 analytical projects are available in the online forum communities, much of them remain untapped due to limited overview and profiling that focuses on COVID-19 analytic techniques. Thus, it is quite challenging for information diggers and researchers to distinguish the recent trends and challenges of COVID-19 analytic for initiating different and critical studies to fight against the coronavirus. This paper presents the findings of a study that executed a web mining process on COVID-19 data analytical projects from the Stack Overflow and GitHub online community platforms for data scientists. This study provides an insight on what activities can be conducted by novice researchers and others who are interested in data analysis, especially in sentiment analysis. The classification results via Naïve Bayes (NB), support vector machine (SVM) and logistic regression (LR) have returned high accuracy, indicating that the constructed model is efficient in classifying the sentiment data of COVID-19. The findings reported in this paper not only enhance the understanding of COVID-19 related content and analysis but also provides promising framework that can be applied in diverse contexts and domains.
A decentralized HC-ADMM approach for large antenna arrays Jyothi B. R.; Manjanaik Naganaik
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp795-805

Abstract

This work addresses the evolving landscape of internet of things (IoT) applications and large antenna array systems, where optimizing spectral efficiency and simplifying design complexities are crucial. Focusing on two key challenges, the study introduces a novel hybrid analog-digital transceiver strategy tailored for frequency-selective channels. By integrating Shannon and Hartley theorems, the approach enhances data transfer rates, thereby optimizing radio frequency (RF) chain utilization in large-scale antennas. To achieve a balance between transceiver performance and hardware complexity, the study employs a decentralized alternating direction method of multipliers (ADMM) framework. The proposed hybrid consensus ADMM algorithm (HC-ADMM) ensures efficient convergence in decentralized optimization scenarios. Comparative analyses with ADMM and existing system transceiver optimization (ESTO) models highlight HC-ADMM's superior performance across key metrics such as spectral efficiency, efficiency per cell, total efficiency, and optimal scheduling of user equipment (UEs). Particularly notable is HC-ADMM's advanced optimization capabilities as the number of transmit antennas increases, positioning it as a promising approach for enhancing overall communication network performance.
A randomized blockchain consensus algorithm for enhancing security in health insurance Najah Al-Sarayrah; Nidal Turab; Abdelrahman Hussien
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1304-1314

Abstract

Health insurance fraud is a significant problem affecting insurance providers and policyholders. To address the rising problem of fraudulent activities in the health insurance sector, this paper proposes a pioneering blockchain-based system aimed at increasing transparency and security. Utilizing a hybrid Blockchain architecture, the system incorporates a consensus algorithm influenced by practical byzantine fault tolerance (PBFT) and proof of activity (PoA) to ensure reliability and efficiency in distributing mining power. Developed using Python, extensive testing confirms the system's performance and security metrics. Results show that a block size containing one transaction is 1.63 KB, with 1.2 KB for data and 0.43 KB for identification and hashing. Operational tests demonstrate that a single participant can upload 850 transactions to the transaction pool, with validation completed in just 7.49 seconds. Block appending time for these transactions is a swift 10 seconds. Notably, the system exhibits resilience against data tampering, detecting unauthorized changes within 881.3 milliseconds across 10,000 blocks and identifying irregularities in the transaction pool within 8.78 seconds. Additionally, to enhance data privacy, patient information is accessible only through a unique QR code, providing an extra layer of security; this research represents a significant advancement in combatting fraud and safeguarding data privacy.
Predicting child alimony under Islamic shariah law using hybrid fuzzy inference system Nur Aqilah Khadijah Rosili; Rohayanti Hassan; Noor Hidayah Binti Zakaria; Farid Zamani Che Rose; Shahreen Kasim; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1367-1375

Abstract

This paper proposes a novel approach to predicting child alimony under Islamic Shariah law using a hybrid fuzzy inference system, integrating Mamdani and Takagi-Sugeno-Kang (TSK) fuzzy systems. Machine learning algorithms have become valuable tools for legal decision-making, but judicial process delays can lead to adverse effects. Our model aims to expedite decision-making and minimize legal fees by accurately determining the proper amount of alimony for children after divorce. We collected data from 94 alimony cases and evaluated the model’s performance using accuracy, precision, recall, and F1 score metrics. The hybrid fuzzy system achieved promising results with 88% accuracy, 84% precision, 89% recall, and an 86% F1 score. Notably, the model reduced bias and standardization in decision-making, promoting fairness. However, the study suggests potential areas for improvement and emphasizes trans-parent judgment processes and coordination among judges in assessing alimony costs based on sufficiency and ma’ruf criteria. This research significantly contributes to machine learning applications in the judicial domain. It provides a valuable decision-making tool for judges and lawyers to enhance the judicial process’s efficiency and ensure children’s welfare in divorce cases under Islamic Shariah law. Further research can enhance the model’s effectiveness and reliability, opening avenues for continued exploration in this field.
Modeling of web-based collaborative learning management system Youssef Lahmadi; Mohammed Ouadoud; Hasnae Mouzouri; Lahcen Oughdir
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1002-1009

Abstract

The challenges faced by most learning management systems (LMS) can be classified into two main areas: pedagogical and technical issues. A comprehensive exploration of these interrelated challenges provides valuable insights for developing a new and more effective model for LMS. In this paper, a novel conceptual model for a web-based collaborative LMS is introduced, merging two distinct learning theories: behaviorism and social constructivism. Through an analysis of the strengths and limitations of each theory, the study moves on to outline the fundamental principles and technical features of the proposed LMS model, which stems from this integration. In conclusion, the paper explores the implications of creating user-centered LMS solutions, with a specific focus on addressing the varied requirements of learners.
Multilevel inverter: harmonic analysis with and without filters for RL load using SPWM techniques Champa Patanegere Nagarajappa; Abhay Anandarao Deshpande
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp756-767

Abstract

Multilevel inverter (MLI) gains more attraction compared to conventional inverter as it generates a staircase output voltage that mimics sine waves of desired output voltage. Cascaded H-bridge (CHB) topology is taken into consideration owing to several benefits over conventional inverters. Various levels of CHB (3 and 5 level) inverters are compared on diverse parameters. In this paper level shift sinusoidal pulse width modulation technique is considered resulting in reduced lower order harmonic (LOH) distortion and improve the quality of output current and voltage depending on the load. Since, the LOH are too dangerous for power electronic circuits. An attempt to shift all the LOH above 50th order depending on the modulation technique with analogy for selecting an appropriate switching frequency is highlighted. The effect of change in switching frequency and modulation index (MI) on RMS output voltage, % voltage total harmonic distortion (VTHD), output power factor with different modulation techniques such as phase disposition pulse width modulation (PsD PWM), phase opposite disposition (POD PWM), alternative phase opposition disposition (APOD PWM) is portrayed in the paper. Further, to boost the performance a unique filter circuits with optimal design values of Inductance and capacitance driven with IEEE 519-2022 standards. The effectiveness in terms of with and without filter is verified and validated using MATLAB.
Exploring corpus linguistics via computational tool analysis: key finding review Wan Nur Aida Sakinah Wan Jusoh; Norfaizah Abdul Jobar; Md Zahril Nizam Md Yusoff; Hanifah Mahat
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1052-1062

Abstract

Corpus linguistics investigates language using extensive text databases. Tools assist researchers in analyzing, extracting, and interpreting linguistic information efficiently. Furthermore, if researchers only use traditional tools in corpus linguistic analysis, they will lack the comprehensiveness and efficiency required to effectively navigate and derive valuable insights from language data. This paper employed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach to find the primary data based on a few keywords in corpus linguistic, corpus analysis, computational linguistic, text corpora and tool support. Based on this method, we used advanced searching techniques on Scopus and Web of Science (WoS) and discovered (N=28) data pertinent to the study. Expert scholars decide on a theme based on the problem, which is (i) types of corpus tools and their uses; (ii) their contributions and their capabilities (iii) limitations of corpus tools. All the tools were used in interdisciplinary studies. In summary, this systematic review uncovers pivotal key findings at the intersection of computational tools and corpus analysis, enriching linguistic knowledge. It highlights the interdisciplinary potential of corpus-based analysis in advancing linguistic tools and, their applications, as well as language analysis.
Analysis of effect of annealing at high temperature on nickel oxide and zinc oxide thin film for solar cell applications Iskandar Dzulkarnain Rummaja; Nur Afiqah Hani Senin; Muhammad Idzdihar Idris; Zarina Baharudin Zamani; Radi Husin Ramlee; Luke Bradley
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp777-787

Abstract

The use of thin films in solar cell technology has gained substantial interest because of their potential for cost-effective and efficient energy conversion. nickel oxide (NiO) and zinc oxide (ZnO) have been used as potential materials in solar cells application especially third generation solar cells because of their good characteristics, such as high electrical conductivity, chemical stability, resistance to degradation, and abundance and low cost. However, at high temperatures, both NiO and ZnO can undergo thermal decomposition and exhibit crystal defects and grain boundaries. This work investigates high temperature annealing on the morphology, structural, and optical properties of NiO and ZnO thin films. The deposited material was annealed at 500 ℃, 600 ℃, and 700 ℃ and be characterized via scanning electron microscopy (SEM), XRD, and UV-Vi’s spectroscopy. The results showed that inceasing the annealing temperature can improve both ZnO and NiO thin films in structure and appearance. For ZnO, higher temperatures made the grains bigger and more orderly, and for NiO, the process made the grains more organized, bigger in size, and spread out more evenly. However, annealing at high temperature yields a smaller bandgap energy value for both thin films.
A novel FFNN-AHO hybrid predictive model for enhancing the performance of jet-cooled PVT system Mohamed A. Essa; Alaa M. Rashad; Ahmed Y. Hatata
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp711-725

Abstract

Photovoltaic-thermal (PVT) systems are common in the conversion of solar energy to electrical and thermal energy. The performance of such systems depends on the environmental conditions in which these systems are applied. This paper presents a parametric study of a jet-cooling PVT system with a staggered distribution of the jets. A feedforward neural network (FFNN) is proposed as a novel predictive model for analyzing the characteristics of the PVT system and its thermal and electrical performance. Moreover, a novel optimization algorithm called archerfish hunting optimizer (AHO) is applied to obtain the optimal structure and elements of the proposed FFNN. The PVT system variables considered as inputs to the FFNN-AHO model are flow rate, wind speed, solar irradiance, and ambient temperature. The average temperature of the PV reaches a maximum of 45.84 ºC, and the maximum temperature un-uniformity reaches to 3.59 ºC. The studied PVT system achieved maximum electrical, thermal, and overall efficiencies of 14.23%, 54.43%, and 68.1%, respectively. Moreover, the results demonstrate that the FFNN-AHO hybrid model provides highly accurate PVT system performance prediction. The correlation coefficient between the actual and predicted data is close to 1, indicating a strong correlation and confirming the reliability and effectiveness of the FFNN-AHO model.
MobileNetV2-D and multiple cameras for swiftlet nest classification based on feather intensity Denny Indrajaya; Hanna Arini Parhusip; Suryasatriya Trihandaru; Djoko Hartanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 2: May 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i2.pp1144-1158

Abstract

MobileNetV2-D is a modified version of MobileNetV2, which is the novelty of this article. The algorithm is used to classify swiftlet nests into seven classes. In 2023, PT Waleta Asia Jaya is required to achieve a 7-fold increase in the export quota of swiftlet nests. To meet the quota, the company made a machine that can recognize swiftlet nest objects, which are classified into seven classes based on feather intensity, namely BRS, BR, BST, BS, BBT, BB, and BB2 for the light feathers to the heavy feathers, respectively. The input image is a combination of four images from four cameras with different positions, which adds to the novelty of MobileNetV2-D for the particular problem here. From the evaluation that has been carried out, the accuracy value of the MobileNetV2-D model was better than the MobileNetV2 model, i.e., the accuracy value of the MobileNetV2-D model was 99.9928% for the training dataset and 94.0723% for the testing dataset. Moreover, the speed of MobileNetV2-D is better than MobileNetV2- architecture.

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