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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
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Collaborative learning through virtual tools: Analysis of the perception of student satisfaction of teaching performance Omar Chamorro-Atalaya; Belmira Marcelo-Veliz; Guillermo Morales-Romero; Nicéforo Trinidad-Loli; Darío Villar-Valenzuela; Beatriz Caycho-Salas; César León-Velarde
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1082-1090

Abstract

The objective of this article is to identify the results of the evaluation of collaborative learning through technological tools as part of the pedagogical strategies in the virtual teaching process. For the evaluation, the SERVQUAL model was used, through which it was identified that 97.73% satisfactorily evaluate the reliability and security of pedagogical strategies through technological tools used in collaborative learning in the teaching process in virtual environments. The optimal evaluation regarding the reliability of collaborative learning is 100% related to compliance with the syllable, to the teacher's disposition to help them in the use of technological tools and to the conformity of the technological tools used in the subject. Regarding the security of collaborative learning, 100% of the satisfactory evaluation is related to the trust and kindness that the teacher transmitted with the use of technological tools in teaching in virtual environments.
A simple architecture for high performance class-D audio amplifier with novel RC network as negative feedback loop Nour El Imane Bellili; Khaled Bekhouche
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp707-713

Abstract

In this work, we have designed and simulated a proposed architecture and good performances single-ended class-D audio amplifier (CDA). The proposed circuit is build using pulse-width modulation (PWM). We have proposed a novel RC network as negative feedback loop attached to a second-order integrator to get free of high-frequency carrier ripples and to reach improved output accuracy, thus improved performance and efficiency. This proposed negative feedback loop extremely reduces total harmonic distortion plus noise (THD+N). We have used a passive second-order butterworth output filter. This circuit fulfills a power supply rejection ratio (PSRR) of 75 dB, a THD+N of 0.004%, 3 times less than attained by usual feedback loop. The proposed circuit with quiescent current of 0.02 mA, signal to noise ratio (SNR) of 89 dB, and peak efficiency of 90% is running at 400 kHz switching frequency. The results of simulation demonstrate that this circuit significantly keeps up with the performance of other circuits but taking advantage of its simple architecture.
Improved cluster to normal ratio protocol for increasing the lifetime of wireless sensor networks Abraham S. Martey; Ebenezer Esenogho
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1135-1147

Abstract

The wireless sensor network (WSN) is a decentralized network that allows sensor nodes to freely join and quit the network, making it a unique network type that varies from centralized systems in which the fusion center decides on entry and exit. However, one of the key drawbacks of these networks is that the sensor nodes are small and located in remote areas. As a result, energy usage must be efficiently managed. In order to limit energy consumption, an efficient clustering protocol approach is necessary, which may be performed by dividing the networks into clusters and selecting cluster heads depending on the remaining energy and sensor distance. The energy hole problem has an impact on the performance of an energy-efficient technique. As a result, this work aims to extend the lifespan of WSNs, the goal of this research is to make the cluster to normal ratio (CTNR) Protocol better. Data forwarding nodes are added to the CTNR protocol hierarchy to enable hopping and avoid consuming nodes in order to solve the energy hole problem (sink). The proposed method is implemented in Matlab, and the results are compared to literature on energy usage and the amount of dead and living nodes. In terms of the performance indicators given, the results reveal that our proposed scheme beat others.
Modeling the impact of jamming attacks in the internet of things Imane Kerrakchou; Sara Chadli; Yassine Ayachi; Mohammed Saber
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1206-1215

Abstract

Security is a key requirement in the context of the Internet of Things. The IoT is connecting many objects together via wireless and wired connections with the goal of allowing ubiquitous interaction, where all components may communicate with others without constraints. The wireless sensor network is one of the most essential elements of IoT concepts. Because of their unattended and radio-shared nature for communication, security is becoming an important issue. Wireless sensor nodes are susceptible to different types of attacks. Such attacks can be carried out in several various ways. One of the most commonly utilized methods is Jamming. However, there are also some other attack types that we need to be aware of, such as Tampering, Wormhole, etc. In this paper, we have provided an analysis of the layered IoT architecture. A detailed study of different types of Jamming attacks, in a wireless sensor network, is presented. The packet loss rate, energy consumption, etc. are calculated, and the performance analysis of the WSN system is achieved. The protocol chosen to evaluate the performance of the WSN is the S-MAC protocol. Different simulations are realized to evaluate the performance of a network attacked by the different types of Jamming attacks.
Artificial intelligent controller-based energy management system for grid integration of PV and energy storage devices Durga Prasad Ananthu; Neelshetty K.; M. Venkateshkumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp617-628

Abstract

In the modern world, photovoltaic (PV) energy generation is becoming more prevalent and cost-effective. To address climate change, many countries have prioritised photovoltaics and made significant investments in energy generation. Because of its non-linear nature, solar energy generation is extremely difficult. This is completely dependent on the solar radiation and the outside temperature. The maximum power generation of a PV system in non-linear weather circumstances and the grid integration of PV with power management are discussed in this article. Artificial intelligence (AI) is vital for improving the energy output of PV systems across a wide range of environmental conditions because traditional controllers do not aid a solar system in producing the maximum energy. The grid integration of PV and EMS (energy management systems) was covered in the later part of this article. In this paper, artificial intelligence is used to provide customers with continuous power through a battery system, which plays a critical role in energy management. Furthermore, the suggested model was simulated in Matlab and its performance was evaluated under various operational scenarios. To demonstrate the effectiveness of the proposed system, the results are compared to IEEE 519.
Cuckoo search algorithm and particle swarm optimization based maximum power point tracking techniques Sally Abdulaziz; Galal Atlam; Gomaa Zaki; Essam Nabil
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp605-616

Abstract

Increasing the efficiency of photovoltaic (PV) systems is a pressing issue, and several studies have focused on the Maximum Power Point Tracking (MPPT) techniques to extract the maximum PV output power. Many MPPT techniques have been discussed in the last decade, and optimization-based MPPT techniques have shown better performance than other MPPT techniques. In this study, two optimization techniques, the cuckoo search algorithm and particle swa9rm optimization with changing inertia weight techniques are discussed and applied to a PV system to track the maximum power point. The MSX-60 PV module and boost DC-DC converter are used in this paper to simulate and model the MPPT system using MATLAB/Simulink to show which technique has the best performance under various solar irradiation scenarios. In addition, different structures of PV arrays such as series-parallel, bridge link, and total cross-tied PV structures are simulated to analyze their effect on the efficiency of MPPT processes.
Analysing corporate social responsibility reports using document clustering and topic modeling techniques Nik Siti Madihah Nik Mangsor; Syerina Azlin Md Nasir; Wan Fairos Wan Yaacob; Zurina Ismail; Shuzlina Abdul Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1546-1555

Abstract

Corporate social responsibility (CSR) has become an imperative tool to address challenges and achieve sustainable growth. Realizing its impact to the society, companies are demanded to participate in sustainable development of which poverty eradication is one of it. The CSR practice, to date, is not strategically planned and executed especially when it comes into philanthropic corporate social responsibility (PCSR). This could be due to failure to identify categories of PCSR activities, limiting its effectiveness to achieve the intended outcomes. Thus, document clustering is proposed to be used to automate the pattern identification process. This study has extended document clustering by integrating the traditional document clustering application with topic modeling approach. This integrated approach enables the identification of the PCSR pattern. The analysis involved a three-year data from the annual report of the 25 CSR-award winning companies in Malaysia which involved several steps. Findings from this study revealed seven clusters that represented seven types of PCSR activities performed by the CSR-award winning companies in Malaysia. The findings offer an insight to be considered by companies in strategizing the CSR activities, particularly philanthropic responsibility in ensuring optimum impact to innovatively support the society and contribute towards poverty mitigation.
Predicting customers churning in banking industry: A machine learning approach Amgad Muneer; Rao Faizan Ali; Amal Alghamdi; Shakirah Mohd Taib; Ahmed Almaghthawi; Ebrahim Abdulwasea Abdullah Ghaleb
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp539-549

Abstract

In this era, machines can understand human activities and their meanings. We can utilize this ability of machines in various fields or applications. One specific field of interest is a prediction of churning customers in any industry. Prediction of churning customers is the state of art approach which predicts which customer is near to leave the services of the specific bank. We can use this approach in any big organization that is very conscious about their customers. However, this study aims to develop a model that offers a meaningful churn prediction for the banking industry. For this purpose, we develop a customer churn prediction approach with the three intelligent models Random Forest (RF), AdaBoost, and Support Vector Machine (SVM). This approach achieves the best result when the Synthetic Minority Oversampling Technique (SMOTE) is applied to overcome the unbalanced dataset and the combination of undersampling and oversampling. The method on SMOTED data has produced excellent results with a 91.90 F1 score and overall accuracy of 88.7% using RF. Furthermore, the experimental results show that RF yielded good results for the full feature-selected datasets.
Data-driven optimal antenna planning for enhanced 4G mobile networks under realistic environment Seifu Girma Zeleke; Beneyam Berehanu Haile; Ephrem Teshale Bekele
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1436-1443

Abstract

Recently different capacity boosting technologies, including 3D beamforming and expanding operating bandwidth have been investigated and included in the enhanced fourth generation (4G) and fifth-generation standards. For mobile operators to enhance their network performance, applying these advanced technologies is vital. To achieve that, planning and optimization work need to consider the spatiotemporal distribution of users. Although the capacity impact of advanced antenna technologies is investigated well, deployment options to exploit their benefits in a cost-effective manner considering a realistic network environment are seldom reported. This work presents a data driven and multi-objective based optimal vertical beams placement for an enhanced 4G mobile network with the newly introduced C-band. The method is utilized for an area located in Addis Ababa, Ethiopia, taking into account the existing 4G mobile network as a reference configuration. Users are distributed based on the data collected by ethio-telecom network management system. Findings indicate that optimal vertical beams placement achieved for gradual deployment with consideration cell edge and aggregate throughput performances while reducing network cost. While being cost-effective, up to 69.2% and 73.8% cell edge performance gain is achieved at 20 and 30 pareto points relative to an existing macro mobile network.
Overcoming camera instability problem for detecting and tracking moving objects in video using reduced data Jalal H. Awad; Balsam D. Majeed
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1589-1598

Abstract

Moving objects detection is a vital field of study in various applications. Many of such applications may have to capture and process a lot of data, then such these data need to be reduced as much as possible in order to have a reasonable and suitable system for achieving the desired aims efficiently. The proposed algorithm utilizes singular value decomposition (SVD) and Bayer pattern filter for their good properties in producing very representative reduced data. This data is then handled by frame difference objects detection, which in turn is an approach that doesn’t need to handle much data. The camera shaking which can be caused by a windy weather in the case of the outdoor static camera may introduce a frame difference with imprecise moving objects detection, hence frames compensation is conducted utilizing a transformation based on speed up robust feature transform (SURF) detected key points.

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