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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 72 Documents
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Search results for , issue "Vol 12, No 6: December 2023" : 72 Documents clear
Real-time lecture's micro-quality assessment for diabetic students based on IoTs and real-time cloud computing technologies Al-Muttairi, Alaa Imran; Abdul-Rahaim, Laith Ali; Thahab, Ahmed Toman
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5641

Abstract

Students with diabetes mellitus require more academic attention, intensive flow up, and a moderate temperature environment during classes. In this paper, the learning process for those students is improved by using the internet of things (IoTs) and cloud computing technologies. The proposed system improves lecture quality using lecture micro quality which is based on lecture time segmentation. Therefore, the designed system provides each student with a microcontroller-based node to collect information about his understanding status in a real-time fashion. Based on this information, the system provides the lecturer with real-time statistical calculations about vital parameters such as the understanding status of each student, the level of the classroom's understanding ratio, and the total number of students who did not understand the topic which is being explained. The designed system is practically tested in a real classroom environment. The implemented system is practically tested in a real classroom environment and the obtained results showed up an improvement in lecture quality due to the real-time feedback which informed the lecturer to adapt the learning technique.
Estimation of hourly solar irradiation on tilted surfaces Belsky, Aleksey; Glukhanich, Dmitry; Sutikno, Tole; Hatta Jopri, Mohd
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6513

Abstract

Tilted photovoltaic panel (PVP) are extensively utilized in solar power installations. To model and design them, you must understand the solar irradiation on a tilted surface over time scales of an hour, day, week, month, or other period. However, most  meteorological stations only record global horizontal irradiance (GHI). In this research, a method is proposed for translating hourly worldwide horizontal irradiation from the NASA POWER database into hourly global sun irradiation on a tilted surface utilizing regression analysis methods and numerical modeling methods based on an isotropic model of solar irradiation. In addition, this work proposes a method for establishing the regression reliance of the diffuse transmittance index on the  clearness index for geographic areas where this relationship has not yet been empirically proven. To assess effectiveness, the results of the proposed technique and other authors' methods are compared with monthly average NASA POWER climatological data using evaluation methods such as mean bias error (MBE), mean absolute bias error (MABE), and root-mean-square error (RMSE). The study's findings can be used to construct, optimize, or anticipate the functioning of solar power facilities at any angle of tilt and in any geographic area.
Security analysis of encrypted audio based on elliptic curve and hybrid chaotic maps within GFDM modulator in 5G networks Mohammed Ameen, Mohammed Jabbar; S. Hreshee, Saad
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4913

Abstract

Wireless communications face significant security challenges, so there is an ongoing necessity to develop an appropriate security strategy to protect data from eavesdroppers using cryptography based on chaos theory. Generalized frequency division multiplexing (GFDM) is a modern multicarrier waveform adaptable to 5G requirements, but its security issues have not been considered. Therefore, this paper proposed an efficient security technique within the GFDM modulator to protect the audio transmission against eavesdropping in 5G networks. The proposed GFDM is achieved by separating the subsymbols for the subcarrier into real and imaginary parts and combining them using a mixture of elliptic curve-linear congruential generator sequence (EC-LCG) with Ikeda and Tent maps, respectively. After that, the subsymbols of each subcarrier are permuted independently using the Duffing map. The effectiveness of the proposed approach to resist attacks was tested, and findings that were achieved are histogram, signal to noise ratio (SNR=-27.8068), spectral segment SNR (SSSNR=-34.9912), peak SNR (PSNR=0.9142), frequency weighted log spectral distance (dFWLOG=37.498), cepstral distance (dCD=9.0176), mean square error (MSE=0.82097), keyspace, and speed. These results show that the proposed model provides a high-security level, high speed in the encryption/decryption, large keyspace, and high sensitivity to the initial conditions.
Machine learning-based PortScan attacks detection using OneR classifier Kareem, Mohammed Ibrahim; Jawad Kadhim Abood, Mohammad; Ibrahim, Karrar
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.4142

Abstract

PortScan attacks are a common security threat in computer networks, where an attacker systematically scans a range of network ports on a target system to identify potential vulnerabilities. Detecting such attacks in a timely and accurate manner is crucial to ensure network security. Attackers can determine whether a port is open by sending a detective message to it, which helps them find potential vulnerabilities. However, the best methods for spotting and identifying port scanner attacks are those that use machine learning. One of the most dangerous online threats is PortScan attack, according to experts. The research is work on detection while improving detection accuracy. Dataset containing tags from network traffic is used to train machine learning techniques for classification. The JRip algorithm is trained and tested using the CICIDS2017 dataset. As a consequence, the best performance results for JRip-based detection schemes were 99.84%, 99.80%, 99.80%, and 0.09 ms for accuracy, precision, recall, F-score, and detection overhead, respectively. Finally, the comparison with current models demonstrated our model's proficiency and advantage with increased attack discovery speed.
Fuzzy logic-based synchronization control system of generators under conditions of frequency instability M. Al-Soud, Mahmoud; M. Eial Awwad, Abdullah; Al-Quteimat, Alaa; Ushkarenko, Oleksandr
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5921

Abstract

This article focuses on studying and addressing the issue of synchronizing diesel gas generator units (DGGU) in autonomous electric power system (AEPS) in the presence of significant voltage frequency fluctuations. MATLAB models of AEPS are being developed that will enable the study of generator connection procedures while operating under a full load. Fluctuations in the rotation frequency of a diesel gas unit can be simulated by generating a realistic random procedure and adding this random signal to the control circuit. In the present study, the authors simulated the generator synchronization process in the presence of random disturbances. This simulation results indicated that the presence of random voltage frequency fluctuations and a nonzero response time of the circuit breaker (which connects the generator to the bars of the main distribution board) may violate the synchronization conditions and result in significant current surges and voltage sags at the time of synchronization. In the present work, a block diagram of the generator synchronization system is proposed that uses fuzzy logic to control the synchronization process. Software tools were developed using the methods of conceptual simulation to control the generator synchronization process; these tools represent an automated operator working station.
Detection of Indonesian wildlife sales and promotion through social media using machine learning approach Lestarini, Dinda; Rusdy, Taufiqurrahman; Iriyani, Silfi; Raflesia, Sarifah Putri
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5418

Abstract

Social media is one of the communication media that is widely used in the digital era as it is today. The use of social media allows people who are far apart to communicate and exchange media, both voice, video, and images quickly and even in real-time. In the past, the sale of protected animals was mostly done on the black market, usually involving a supply chain between sellers that usually existed in traditional markets or certain communities. With the existence of social media, the trend in conducting transactions and promoting wild animals has shifted from traditional to modern thanks to the support of existing technology. Protected wild animals are of concern to the local government or the global world to protect their existence. Therefore, this research proposes a machine learning (ML) based approach to detect the promotion and sale of wild animals on social media. The implementation of Naïve Bayes classifier (NBC) has a high accuracy in detecting trade in wild animals on social media with an accuracy value of 86. The implementation of ML-based approach is expected to produce new technology that allows authorities to know and monitor social media in order to reduce the sale and promotion of protected wildlife.
A highly scalable CF recommendation system using ontology and SVD-based incremental approach Mhammedi, Sajida; Gherabi, Noreddine; El Massari, Hakim; Sabouri, Zineb; Amnai, Mohamed
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.6261

Abstract

In recent years, the need of recommender systems has increased to enhance user engagement, provide personalized services, and increase revenue, especially in the online shopping industry where vast amounts of customer data are generated. Collaborative filtering (CF) is the most widely used and effective approach for generating appropriate recommendations. However, the current CF approach has limitations in addressing common recommendation problems such as data inaccuracy recommendations, sparsity, scalability, and significant errors in prediction. To overcome these challenges, this study proposes a novel hybrid CF method for movie recommendations that combines the incremental singular value decomposition approach with an item-based ontological semantic filtering approach in two phases, online and offline. The ontology-based technique is leveraged to enhance the accuracy of predictions and recommendations. Evaluating our method on a real-world movie recommendation dataset using precision, F1 scores, and mean absolute error (MAE) demonstrates that our system generates accurate predictions while addressing sparsity and scalability issues in recommendation system. Additionally, our method has the advantage of reduced running time.
Implemantation of firefly algorithm on Arduino Uno Dewatama, Denda; Melfazen, Oktriza; Fauziyah, Mila
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5362

Abstract

Not only getting the optimal solution of a problem, embedding the algorithm on the microcontroller is also expected to work optimally without burdening the system and fast response. Getting a microcontroller specification that matches the complexity of an algorithm is necessary so that the system can execute the algorithm perfectly. Values for the basic parameters of optimization algorithms inspired by nature such as the firefly algorithm (FFA) which are interpreted into variables greatly affect the performance of the microcontroller in obtaining the expected optimal solution. The observed performance of the Arduino Uno microcontroller in running the FFA includes execution time and memory capacity required to obtain optimal values based on changes in absorption coefficient, random parameters, iterations, and population. Changes in the absorption coefficient and random parameters affect the optimal value but do not significantly affect the execution time and memory capacity of Arduino Uno. Iteration changes greatly affect execution time and population changes most affect the performance of Arduino Uno. With a dynamic memory capacity of 2 Kb, the FFA can be run with a maximum range of 50 populations and up to 20 iterations.
Energy efficient clustering-based routing algorithm for internet of things Saad, Aya; Hegazy, Islam; M. El-Horbaty, El Sayed
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5169

Abstract

Routing process is one of the most critical processes in wireless sensor network (WSN). Due to WSN is mainly used in many applications in internet of things (IoT), routing algorithm can affect the performance of these applications. Thus, the usage of inefficient routing algorithm may lead to losing the data collected by sensors. Moreover, it will cause the sensors to waste energy. This paper proposes an energy efficient clustering-based routing algorithm that is based on tunicate swarm algorithm (TSA). TSAbased clustering algorithm selects the optimal cluster head by calculating the remaining energy, the distance to the base station (BS), the distance to each cluster member and balancing the load between the created clusters. TSAbased routing algorithm is used to create paths from cluster heads to the BS using relay nodes. The TSA-based routing algorithm creates the paths based on the path length, the count of relay nodes in the path, and the number of cluster members of each relay node. The result shows that the proposed algorithm is promising in respect of extending the lifetime of the network and conserving the energy.
Performance enhancement of 5G uplink MIMO over fading-shadowing, path losses, and ISI using LZF equalize Q. Hameed, Ashwaq; H. Numan, Ali
Bulletin of Electrical Engineering and Informatics Vol 12, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i6.5105

Abstract

The challenges of the 5G mobile wireless communication systems transmission channels have been changed continuously because of the signal transfer path characteristics such as real-time applications, path loss, multiple users, reflected rays, channel Rayleigh-fading, shadowing, noise, and inter symbol interference (ISI). These challenges have been treated to reach the minimum bit error rate (BER) value of the received data and maximum data rate of high-speed wireless mobile communication systems. In this paper, the linear zero-forcing (LZF) equalizer with uplink multi-input multi-output (MIMO) system has been proposed to enhancement the BER, which is caused by the ISI, Rayleigh fading, shadowing, path losses, and additive white gaussian noise (AWGN). Furthermore, the proposed approach is applied to a different number of antennas constellation to show the effect of increasing the number of antennas on the BER. The results show that the proposed LZF equalizer-MIMO system model has reached lower BER values, and high performance with an increase in the receiver to 8×14, 8×16 and 8×18 antennas constellation at 8, 10, 12, 14, 16, and 18 dB signal to noise ratio (SNR).

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