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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 9,174 Documents
 723   724   725   726   727 
A systematic review of structural equation modeling in augmented reality applications Vinh The Nguyen; Chuyen Thi Hong Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp328-338

Abstract

The purpose of this study is to present a comprehensive review of the use of structural equation modeling (SEM) in augmented reality (AR) studies in the context of the COVID-19 pandemic. IEEE Xplore Scopus, Wiley Online Library, Emerald Insight, and ScienceDirect are the main five data sources for data collection from Jan 2020 to May 2021. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach was used to conduct the analysis. At the final stage, 53 relevant publications were included for analysis. Variables such as the number of participants in the study, original or derived hypothesized model, latent variables, direct/indirect contact with users, country, limitation/suggestion, and keywords were extracted. The results showed that a variety of external factors were used to construct the SEM models rather than using the parsimonious ones. The reports showed a fair balance between the direct and indirect methods to contact participants. Despite the COVID-19 pandemic, few publications addressed the issue of data collection and evaluation methods, whereas video demonstrations of the augmented reality (AR) apps were utilized. The current work influences new AR researchers who are searching for a theory-based research model in their studies.
Energy efficient with prolonging lifetime in homogeneous wireless sensor networks Shaimaa Hadi; Hayder Rahm Dakheel; Atyaf Jarullah Yaseen
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp801-809

Abstract

In this artical, we suggest a new clustering model called the Fuzzy Low Energy Adaptive Clustering Hierarchy Protocol (FLEACH). It has the ability to go around obstacles and fix the issue of uneven energy consumption in homogenous wireless sensor networks (WSNs). In order to determine the best routing path for the homogeneous WSNs, we also suggest the Ant Colony Routing Method (ACORM), which is an energy-efficient routing technique. ACORM aims to investigate issues relating to balancing energy consumption and maximizing network life. To illustrate FLEACH-ACORM's effectiveness in managing energy consumption and optimizing homogeneous network life, we compare our system with two approaches: Power-Efficient Sensor Information Systems (PEGASIS) and LEACH. Results of the simulation indicate that the network lifetime achieved by FLEACH-ACORM could be increased by almost 28.5 % and 19.8 % more than that obtained by LEACHPEGASIS, LEACH clustering protocols, respectively.
Enhanced accuracy for heart disease prediction using artificial neural network Raniya Rone Sarra; Ahmed Musa Dinar; Mazin Abed Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp375-383

Abstract

Making an accurate and timely diagnosis of cardiac disease is critical for preventing and treating heart failure. The accuracy of results produced by traditional machine learning (ML) algorithms is satisfactory. On the other hand, deep learning algorithms result in higher prediction accuracy. In this study, we used an artificial neural network (ANN) model to construct a deep learning diagnosis system for heart disease prediction. The developed ANN prediction model achieved 93.44% accuracy, which is 7.5% higher than a traditional ML model support vector machine (SVM). Additionally, using a simpler neural network reduced the time taken for training and classification to less than a minute.
Enhancement of traveling wave semiconductor optical amplifier approach for DWDM communication system Ahmed A. Amer; Ahmed Abdulelah; Alaa A. Mashkor; Adnan Sabbar
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1541-1547

Abstract

In this study, the high performance of dense wavelength division multiplexing (DWDM) by using a traveling wave semiconductor optical amplifier (TW-SOA) at a channel spacing of 100 GHz is investigated, in terms of (Q-factor, injected current, transmitted power, gain). The Optisystem software is employed to send the different range of input power over the different ranges of the TW-SOA injected current with optimized TW-SOA parameters. The data rate of trans- mission optical signal up to 300 Gb/s at -35 dB input signal power have been investigated. The better results have been measured of the information signal with high quality and gain, when the range of input power is corresponding to the optimized range of injected current for the signal to be transmitted effec- tively. The present communication also supports various numbers of users with the same data rate of 5 Gb/s which is used to check the high quality of the signal in the receiver.
Green-phosphor Ca3Sc2Si3O12:Ce3+ for solid-status illumination: gel-combustion structural and luminous characteristics Huu Phuc Dang; Bui Van Hie; Nguyen Le Thai
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp710-715

Abstract

Ca3Sc2Si3O12:Ce3+ phosphors with one stage and tiny dimension were effectively produced utilizing the gel-combustion technique at a lower heat (1100◦C) than the traditional solid-status reaction technique (around 1500◦C). The phosphors' crystal phase and microstructure, as well as their luminescence, were studied. The particle size is around 1m, which is significantly smaller than what the solid-status process produces. When particles are combined of silicon and deposited on a blue light-emitting diode (LED), finer particles can minimize interior diffusing. A significant green radiation is noticed that is caused by typical Ce3+ transition radiations 5d–2F5/2 and 5d–2F7/2. The stimulation spectra reveal a wide and high absorptivity at around 460 nm, indicating that it would be an excellent color conversion in white LEDs. The gel-combustion phosphor has a decay period of 54.65 ns.
Blockchain for baccalaureate examination sheets protection in Iraq Hayder A. Nahi; Saeed M. Hashim; Dhurgham J. Kreem
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1183-1191

Abstract

Due to their unique qualities, including data integrity, security, decentralization, and dependability, blockchain technologies have drawn a lot of interest from both academia and business. In order to effectively handle the adoption problems of blockchain technologies, it is important to identify what influences their use and adoption. In order to protect the exam sheet (as image format) for the baccalaureate examination in Iraq. This paper article sought to construct a private blockcahin powered by a variety of algorithms, After that, with this concern about privacy and fear of private information leaking, and in order to ensure that that image will only be seen by the specific person you want, the technology is full of many encryption features that achieve this end, we encrypt the image before sending it as a transaction in the Blockchain network. Also, we obtained speed smart contact verifications compared with traditional systems due to the proposed system is private and has simple complexity.
Analysis of the development of fruit trees diseases using modified analytical model of fuzzy c-means method Ali Abdulkarem Habib Alrammahi; Farah Abbas Obaid Sari; Haidar Abdulwahab Habeeb Shamsuldeen
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp358-364

Abstract

The use of digital technologies in agriculture has become very important to ensure the protection of trees from disease and limit their development, which leads to increased production, so the paper proposes a modified analytical model to analyze the data and graphical parts of the leaves of fruit trees using priority fuzzy C-means (PFCM). Based on the proposed distance scale to obtain a clustering with a less error rate and fairly close to accuracy for the purpose of monitoring the development of diseases of fruit trees, by classifying the diseases and medications needed for each disease, a database was created containing large samples of data and images, where the results of Analysis of previous studies that analyzes of large amounts of data give accurate results. The proposed method was used in smart gardens with large areas and we got the desired results.
Comparative analysis of time series prediction model for forecasting COVID-19 trend Sri Ngudi Wahyuni; Eko Sediono; Irwan Sembiring; Nazmun Nahar Khanom
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp600-610

Abstract

The outbreak of the COVID-19 pandemic occurred some time ago, making the world a pandemic. Based on this condition is important to predict early to prevent the COVID-19 disease if someday pandemic occurs. The aim of the study is to compare the analysis result of cumulative cases of COVID-19 using multiple linear regression (MLR), ridge regression (RR), and long short term memory (LSTM) models for cases study Java and Bali islands. We chose both islands as a case study because they have very dense populations. These three models are the most widely used time series-based prediction models and have relatively high accuracy values.  The predictive variables used are the number of cumulative cases, the daily cases, and population density. The research data was taken from Kaggle and processed using google collabs. Data was taken from January 20, 2020, to August 8, 2020, and data training was carried out for 12 days. The results show the accuracy of LSTM is better than other models. it can be seen in the accuracy value (99.8 %) of the model test result. The testing model uses R2, mean square error (MSE), and root mean square error (RMSE).
A new design of 5G multilayers planar antenna with the enhancement of bandwidth and gain Abderrahim Bellekhiri; Noha Chahboun; Jamal Zbitou; Yassin Laaziz; Ahmed El Oualkadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1502-1510

Abstract

In this work, we design a microstrip patch antenna having a dimension of 3.279x4.232 mm2 and consisting of a Foam-like substrate, of a relative dielectric permittivity of 1 and with a width of 0.5 mm, placed between two identical Rogers RT5880 substrates, having a value of 2.2 as relative dielectric permittivity, a loss tangent of 0.0009 and a height of 0.508 mm. The designed antenna resonates at 28 GHz, featuring a maximum gain of 9.77 dBi and a wide frequency bandwidth of 2.9 GHz. Compared to the conventional antenna, this proposed structure achieved an important enhancement of the directivity, with a value around 38.8°. The CST Microwave Studio software was used for all designs and analysis.
Feature selection optimization based on genetic algorithm for support vector classification varieties of raisin Yudi Ramdhani; Dhia Fauziah Apra; Doni Purnama Alamsyah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp192-199

Abstract

Grapes are one of the fruit plants that grow that propagate in certain fields. Grapes can be processed into juice, wine, raisins, and so on. Raisins are dried grapes. Raisins have a distinctive taste and aroma. Raisins are a concentrated and nutritious source of carbohydrates, containing antioxidants, potassium, fiber and iron. To increase the accuracy value, the optimize selection genetic algorithm (GA) is used. This research was conducted modeling using the support vector machine (SVM) and SVM algorithms based on optimize selection GA by using the raisin (raisin varieties) dataset obtained from the UCI machine learning repository. The research dataset is divided into training data and testing data. The data sharing will be carried out using the cross validation and split validation operators. Data validation with 10-Fold-validation on the SVM algorithm has the best level of performance among 5 other algorithms such as; Naïve Bayes, K-nearest neighbor (K-NN), decision tree (DT), neural network, and random forest (RF). The SVM algorithm produces accuracy and area under the curve (AUC) values of 87.11% for accuracy and 0.928 for AUC. Optimization in this study using optimize selection GA. SVM based on optimize selection GA produces accuracy and AUC values of 87.67% for accuracy and 0.930 for AUC.

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