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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
 741   742   743   744   745 
Analysis of single-phase cascaded H-bridge multilevel inverters under variable power conditions Subramani Chinnamuthu; Vinothkumar Balan; Krithika Vaidyanathan; Vimala Chinnaiyan; Premalatha Santhanamari
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1381-1388

Abstract

Easy modular I action is one of the benefits of a cascaded H-bridge (CHB) inverter. This study proposes an only one multilevel inverter comes with a unique H-bridge unit. The structure of the proposed topology is then enhanced in order to make use of switching devices and DC-link voltage inputs while creating a massive number of voltage steps. A cooperative active and reactive power control strategy is offered to earn a better real and reactive power management for every DC voltage source of a photovoltaic (PV) module, as well as boost systems power quality and reliability. A unique control approach and proportional pulse width modulation (PWM) modulation are described for the cascaded H-bridge multilevel inverters for grid-connected systems. Each Hbridge module can give different power levels thanks to this control. To supply the DC source, use the system's proportional, integral and derivative (PID) controller. The functionality and achievements of the proposed scheme with its associated algorithms in production of all operating voltage have been proven using experimental data from a nine-level single-phase inverter. Finally, to construct a cascaded H-bridge nine-level inverter, the proposed control strategy is developed and implemented in MATLAB software.
A new method based on swarm intelligence with encrypted data in wireless sensor networks Dhuha Kh. Altmemi; Basim Sahar Yaseen
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1525-1533

Abstract

Wireless sensor networks (WSNs) technology is one of the most essential Internet of things technologies. It is utilized efficiently in a variety of real-world applications, including healthcare, environmental monitoring, tracking, etc. WSNs are composed of sensor nodes with restricted resources. However, the communication between WSN components is not secure. Therefore, it is necessary to build efficient and lightweight cryptographic algorithms to secure shared data. Our paper comprises proposes a secure protocol called grasshopper optimization algorithm routing protocol (GOARP) with a lightweight encryption method in each sensor called rivest cipher 5 (RC5) to enhance network efficiency and simulation in terms of power consumption, required memory space, and computational time. Subsequently, the network lifetime result achieved in the proposed method is about (70%) more than in GOA elliptic curve cryptographic and Diffie Hellman (GOA-ECCDH).
Detecting translation borrowings in huge text collections using various methods Adel Al-janabi; Ehsan Ali Al-Zubaidi; Baqer M. Merzah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1609-1616

Abstract

The purpose of this work is to investigate the problem of detecting transportable borrowings and text reuse. The article proposes a monolingual solution to this problem: translating the suspicious material into language collections for additional monolingual analysis. One of the major requirements for the suggested technique is robustness against machine learning ambiguities. The next step in the document analysis is split into two parts. The authors begin by retrieving documents-candidates that are similarity to other types of text recurrence. The paper proposes retrieving texts utilizing word clusters formed using distributional semantic for robustness. In the second stage, the authors use deep learning neural networks to compare the suspected document to candidates utilizing phrase embedding. The experimentation is carried out for the language pair “English-Arabic” on both articles and synthetic data.
Principal component analysis in the epidemiology of diarrhoea in calves Ablaikhan Kadyrov; Altay Ussenbayev; Dariyash Kurenkeyeva; Berdaly Kurenkey; Sarsenbay Abdrakhmanov; Nurlan Tashatov
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1762-1770

Abstract

The paper is the first to use principal component analysis (PCA) in veterinary epidemiology and aims to identify the most significant agents of diarrhoea in calves. Data were collected from 245 calves on 32 farms within 13 districts of Northern Kazakhstan. Epidemiological data were simulated in R, using standard PCA modules. The data clustering was carried out based on the prevalence of seven enteropathogens for an age group dataset (represented by four animal groups) and a farm type dataset (by three farm types depending on herd size). The simulation revealed that the components identified here for one and two-week calves explained 91.31% of the variance. The first two components of large and middle-sized farms covered 90.3% of the variance. The coordinates corresponding to pathogens were approximately visualised in directions of eigenvectors for each age group and farm type. The coordinate for Cryptosporidium parvum was in directions of eigenvectors for one-to three-week calves and large farms. The coordinate for rotaviruses was in the direction of eigenvectors for four-week calves and medium-sized and small farms. So, PCA can potentially be useful in the clustering of epidemiological datasets and making decisions on control of infectious diseases with a multi-pathogenic nature.
Feature-based approach and sequential pattern mining to enhance quality of Indonesian automatic text summarization Dian Sa'adillah Maylawati; Yogan Jaya Kumar; Fauziah Binti Kasmin
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1795-1804

Abstract

Indonesian automatic text summarization research is developed rapidly. The quality, especially readability aspect, of text summary can be reached if the meaning of the text can be maintained properly. Therefore, this research aims to enhance the quality of extractive Indonesian automatic text summarization with considering the quality of structured representation of text. This research uses sequential pattern mining (SPM) to produce This research use SPM to produce sequence of words (SoW) as structured text representation using PrefixSpan algorithm. Then, SPM is combined with feature-based approach using sentence scoring method to produce summary. The experiment result using IndoSum dataset shows that even though the combination of SPM and sentence scoring can increase the precision value of recall-oriented understudy for gisting evaluation (ROUGE)-1, ROUGE-2, and ROUGE-L, from 0.68 to 0.76, 0.54 to 0.69, and 0.51 to 0.72. Especially, combination of SPM and Sentence Scoring can enhance precision, recall, and f-measure of ROUGE-L that consider the order of word occurance in measurement. SPM increases ROUGE-L f-measure value of sentence scoring from 0.32 to 0.36. Moreover, combination of sentence scoring and SPM is better than SumBasic that used as feature-based approach in the previous Indonesian text summarization research.
An effective way to generate the shift timing constraints and sanity checks Shaik Mahammad Ameer Afridi; Nagaraja Shylashree; Satish Tunga; Latha Bavikatte Nanjundappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1399-1406

Abstract

Design for testability (DFT) is a technique, which facilitates a design to become testable after fabrication. As the technology node is shrinking, complexity of the system-on-chip (SoC) becomes high and inserting DFT and verifying its timing becomes complex. For these complex SoC, generating DFT timing constraints becomes difficult in shift mode and the time required for the generation of these timing constraints is also more. A new methodology proposed to overcome these issues. The main objective of this work is to propose the flow for generating DFT timing constraints for the complex SoC in shift mode, by dividing the design blocks into scan blocks and non-scan blocks. To target the whole design without getting all paths reported, relaxation of the setup, and hold time for non-scan blocks plays crucial role. If not, the time taken to generate DFT timing constraints would be more. Implemented methodology of this paper includes design setup, timing exceptions, and synopsys design constraints (SDC) generation for DFT timing. Design setup consists of all pre-requisites for design such as netlists, timing libraries, and exceptions. Synopsys primetime (PT Shell) is used for all the timing-related checks. Compared to conventional methods, the proposed flow reduces the overall time by 40% to generate constraints.
Sustainable framework for a geostationary satellite control earth station system using parallel configuration Nur Shazana Abdul Rahman; Nadirah Abdul Rahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1498-1508

Abstract

Earth station system plays an important role to ensure that a satellite communication system runs efficiently. Redundancies of the subsystems and regular maintenance planning can improve the earth station system. Organising system affordability can be challenging as more redundancies would acquire more maintenance. Thus, a sustainable framework that considers an earth station system's reliability, cost, and maintainability was modelled. 2-parallel, 3-parallel, and 4-parallel earth station system configurations were studied with five mean time between failures (MTBF). The results showed that an earth station that was configured with 2-parallel configuration provided an optimum reliability system performance though both 3-parallel and 4-parallel configuration provided higher reliability. Moreover, the 2-parallel configuration was also cheaper in terms of operational cost if compared to the 3-parallel and the 4-parallel configurations. Hence, this sustainable framework comprising the reliability and operational cost elements were modelled based on the 2-parallel configuration with the proposed maintenance activities. Moreover, the computed root mean square (RMS) values for both new reliability and new operational cost models yielded smallest values of 20.84% and 22.82% respectively. Thus, these RMS values for both reliability and operational cost models based on 2-parallel configuration are suitable to be applied in the earth station system design.
Model-driven architecture: generating models from Symfony framework M'hamed Rahmouni; Chaymae Talbi; Soumia Ziti
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1659-1668

Abstract

The web application development industry is constantly growing due to the extensive use of web applications in different devices, most of them run on Android, iOS, and Windows Phone operating systems. However, the development of applications designed for platforms requires more concerns such as code efficiency, interaction with devices, and speed of market penetration. The model-driven approach (MDA) combined with unified modeling language (UML) could provide abstraction and automation for software developers. This paper presents an MDA approach for the development of web applications based on the Symfony framework, UML modeling, model transformation, and then automatic code generation in order to facilitate and accelerate the development of web applications. The first step of this work is to establish the metamodel of Symfony framework and the metamodel of UML class diagram. In the second step, the various transformation rules between the source and target metamodels are first defined. Atlas transformation language (ATL) implements these rules. The result of this transformation is a platform-specific model (PSM) represented by Ecore language. The generated PSM model represents the input model of model-to-code (M2C) transformation for generating the code of web applications. To validate this work, we have implemented a case study.
Students’ satisfaction with the service quality of academic advising systems Ali M. Ghonmein; Khaldun G. Al-Moghrabi; Tawfiq Alrawashdeh
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1838-1845

Abstract

Academic advising (AA) is an integral part of university education, as it has an indispensable role in helping students fulfil their goals in higher education, become responsible for their own learning, and formulate meaningful educational plans that perfectly match the abilities of each student. For this reason, educational institutions around the world are striving to upgrade their AA systems (AAS) to provide their students with personalized experiences. Meanwhile, modern technology can improve the advising process and facilitate the accomplishment of the corresponding tasks. Therefore, the integration of technology into AA not only offers more flexibility for the students but also improves the delivery of advising services. This study aimed i) to identify those factors that mainly affect the AAS services being offered in universities; and ii) to examine how the satisfaction of students with AAS is affected by service quality. A total of 400 students from the Information Technology College of Al-Hussein Bin Talal University (AHU) were invited to participate in an online survey for data collection, and a response rate of 90.50% was recorded. Results show that the satisfaction of students with the AAS is affected by trust, network quality, service quality, system quality, information quality, and perceived risk.
Improving the efficiency of clustering algorithm for duplicates detection Abdulrazzak Ali; Nurul Akmar Emran; Safiza Suhana Kamal Baharin; Zahriah Othman; Awsan Thabet Salem; Maslita Abd Aziz; Nor Mas Aina Md Bohari; Noraswaliza Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i3.pp1586-1595

Abstract

Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a data pre-processing method that increases the efficiency of window algorithms in grouping similar records together. In addition, the proposed method also deal s with the window size problem. In the proposed method, high-rank attributes are selected and then preparators are applied to the selected traits. A compensation algorithm is implemented to reduce the problem of missing and distorted sort keys. Two datasets (compact disc database (CDDB) and MusicBrainz) were used to test duplicates detection algorithms. The duplicates detection toolkit(DuDe) was used as a benchmark for the proposed method. Experiments showed that the proposed method achieved a high rate of accuracy in detecting duplicates. In addition, the proposed method.

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