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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 2,901 Documents
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Sentiment analysis of imbalanced Arabic data using sampling techniques and classification algorithms Al-Khazaleh, Maisa J.; Alian, Marwah; Jaradat, Manar A.
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5886

Abstract

Sentiment analysis is a popular natural language processing task that recognizes the opinions or feelings of a piece of text. Microblogging platforms such as Twitter are a valuable resource for finding such people’s opinions. The majority of Arabic sentiment analysis studies indicated that the data utilized to train machine learning algorithms is balanced. In this paper, we investigated the impact of sampling techniques and classification algorithms on an imbalanced Arabic dataset about people’s perceptions of COVID-19, with the majority of opinions reflecting people’s fear and stress about the pandemic, and the minority reflecting the belief that the pandemic was a hoax. The experiments concentrated on analyzing the imbalanced learning of Arabic sentiments using over-sampling and under-sampling techniques on seven single machine learning algorithms and two common ensemble algorithms from the bagging and boosting families, respectively. Results show that resampling-based approaches can overcome the difficulty of an imbalanced dataset, and the use of over-sampled data leads to better performance than that of under-sampled data. The results also reveal that using oversampled data from synthetic minority over-sampling technique (SMOTE), borderline-SMOTE, or adaptive synthetic sampling with random forest classifier is the most effective in addressing this classification problem, with F1-score value of 0.99.
Load frequency control of interconnected power system using cuckoo search algorithm Mishra, Soumya; Kumar, Pujari Harish; Ramasamy, Rajarajan; Edayillam Nambiar, Renjini; Puvvada, Praveena
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6714

Abstract

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions.
Energy efficiency based RPL protocol using grasshopper optimization algorithm Matada Murigendraiah, Savitha; I. Basarkod, Prabhugoud
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7856

Abstract

The routing protocol for low-power and lossy networks (RPL) is necessary for the internet of things (IoT) because it offers scalable, reliable, and energy-efficient routing capabilities. The trickling algorithm generates a destination-oriented directed acyclic graph (DODAG) with the broadcasting of suppression. However, broadcast suppression is insufficient when addressing network coverage and optimization problems based on uneven node distribution. Network congestion develops in large-scale IoT implementations where many devices are interconnected and congestion causes data transmission delays, decreased overall reliability, and higher latency. In this paper, the grasshopper optimization algorithm with the DODAG (GOA-DODAG) is proposed to determine optimization problems and energy-efficient reliable routing paths which include coverage-based dynamic trickling technique to construct DODAG energy-efficient without affecting the coverage of network and data routing reliability. The GOA-DODAG achieves a 98% packet delivery ratio (PDR) while consuming 0.48 mJ, which is more preferable in comparison to the existing methods like efficient-routing protocol for low-power and lossy networks (E-RPL), reliable and energy-efficient RPL (REFER), elaborated cross-layer RPL objective function to achieve energy efficiency (ELITE).
An extended sensor fault tolerant control method applied to three-phase induction motor drives Huu Nguyen, Minh Chau; Tran, Cuong Dinh
Bulletin of Electrical Engineering and Informatics Vol 13, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i1.5992

Abstract

This research presents a fault tolerant (FT) control method for three-phase induction motor drives (IMDs) against sensor failures in the operating process. In this paper, an IMD applied the field oriented (FO) control for the speed and torque control is used to study the operation under sensor fault conditions. A fault detection isolation function is integrated into the FO control loop as an intermediary component to evaluate the quality of the measured signals of the sensors and provide proper signals for speed control of the drive system. A combined method of a comparison algorithm and a third difference operator (TDO) is proposed for the fault diagnosis function to improve the sustainable operation of the drive. The reliability of the proposed method will be verified through the operation mechanism of the FT function corresponding to three sensor fault states and a random noise state in the simulation environment by MATLAB/Simulink software.
Speed control for traction motor of urban electrified train in field weakening region based on backstepping method Thu Anh, An Thi Hoai; Tung, Ngo Manh
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.5209

Abstract

Tractor motors always operate in the speed region higher than rated speed, but is limited to the module of the stator current, stator voltage vectors. Additionally, mathematical model of traction motor has shown nonlinearity through the product of the state variables ???, ??? with the input variable ??:?????, ?????. Therefore, this paper focuses on the study of speed control of traction motors in weakening field region while optimizing torque control, and choosing the backstepping method in designing speed–flux controller in order to solve the nonlinear structure. The simulation results of the responses: speed, torque, power, and flux performed on MATLAB/Simulink software with parameters collected from metro Nhon-Hanoi Station, Vietnam have proven the correctness in theoretical research.
Multimodal speech emotion recognition optimization using genetic algorithm Michael, Stefanus; Zahra, Amalia
Bulletin of Electrical Engineering and Informatics Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i5.7409

Abstract

Speech emotion recognition (SER) is a technology that can detect emotions in speech. Various methods have been used in developing SER, such as convolutional neural networks (CNNs), long short-term memory (LSTM), and multilayer perceptron. However, sometimes in addition to model selection, other techniques are still needed to improve SER performance, namely optimization methods. This paper compares manual hyperparameter tuning using grid search (GS) and hyperparameter tuning using genetic algorithm (GA) on the LSTM model to prove the performance increase in the multimodal SER model after optimization. The accuracy, precision, recall, and F1 score improvement obtained by hyperparameter tuning using GA (HTGA) is 2.83%, 0.02, 0.05, and 0.04, respectively. Thus, HTGA obtains better results than the baseline hyperparameter tuning method using a GS.
Experimental investigation of a hybrid photovoltaic-thermal energy system for hot air production Hiendro, Ayong; Husin, Fitriah; Taufiqurrahman, Muhammad; Aula, Abqori
Bulletin of Electrical Engineering and Informatics Vol 13, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i3.6823

Abstract

Solar energy as a non-fossil alternative energy source has become the best choice to overcome the problem of energy demand in most countries in the world. There are two different techniques to convert solar energy: photovoltaic (PV) panels to produce electricity and thermal collectors to generate heat. The two technologies can be combined to provide electrical and thermal energy either simultaneously or separately. In order to optimize the performance of a hybrid photovoltaic-thermal (PVT) solar air heater, it is necessary to collect experimental data on solar irradiation and temperature. This paper emphasized the development of a PVT energy system for hot air production in a temperature range of 50-55 °C. Additionally, experiments were constructed to monitor the information acquired from the proposed PVT solar air heater and the environment, such as hot air temperature, ambient temperature, and solar irradiation. The real-time monitoring system was set for five sample days. A microcontroller unit was used to control the hot air temperature and save the measurement data into memory. The experimental results showed that the proposed PVT solar air heater is capable of maintaining a certain level of hot air temperature throughout the day and night.
Resource allocation for device-to-device communications underlaying uplink cellular networks Haroune, Ahtirib; Messaoud, Hettiri; Brahim, Lejdel
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.5773

Abstract

Underlying cellular networks, device-to-device (D2D) communications are a practical network technology that can increase power efficiency and spectrum usage for close-proximity wireless services and applications. However, D2D link interference, when sharing resources with cellular users (CUs), poses a major challenge in such distribution situations. In this research, we primarily utilize wireless channel data that exhibits slowly shifting large-scale fading to conduct spectrum sharing and power allocation. The overall ergodic capacity of all cellular user equipment (CUE) links is initially considered as the optimization target in order to maximize the overall throughput of CUE links while ensuring the reliability of each D2D link. Then, the expansion of the minimum ergodic capacity is measured to ensure a more consistent capacity performance across all CUE links. We utilized algorithms that are resilient to channel fluctuations and produce optimal resource allocation. We use MATLAB, and the computer simulation validates its intended performance.
Securing IoT edge device communication with efficient ECC middleware for resource-constrained systems Mohamed Yusoff, Zainatul Yushaniza; Ishak, Mohamad Khairi; AB Rahim, Lukman
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.7602

Abstract

The internet of things (IoT) rapidly grows into various parts of life. However, it has significant obstacles during setup and deployment, particularly in terms of network segmentation, administration, and security at all tiers, from physical to application. While IoT provides several advanced features and benefits, it is also vulnerable to security threats and flaws that must be thoroughly investigated to avoid misuse. Cryptographic approaches are routinely used to address these security concerns. Message queuing telemetry transport (MQTT), an application layer protocol, is vulnerable to various known and undisclosed security flaws. Integrating encryption techniques within the MQTT protocol to provide secure data flow is a potential strategy for increasing security. This study provides a middleware broker that improves authentication processes, securing connections between cloud servers and resource-constrained devices. Using a Java Servlet and the elliptic curve cryptography (ECC) technique, the study creates a system for creating encrypted identification keys within a web-based transaction framework. This system intends to provide asymmetric authentication that is energy and resource-efficient, with a focus on cost minimization. It also includes a security feature to protect users from common internet threats. The system's efficacy, including its low energy usage of only 4 mJ per device, is thoroughly tested, proving it meets the original protocol criteria.
Deep convolutional neural network for Lampung character recognition Bintoro, Panji; Zulkifli, Zulkifli; Fitriana, Fitriana; Sukarni, Sukarni
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6734

Abstract

Recognition of document based, and handwritten characters has recently emerged as highly relevant field of study in the field of digital image processing. The ability to read and write Lampung script is a crucial competency as it helps preserve the language, which is a part of Indonesian culture. This research utilizes data obtained from classified documents and handwritten samples, categorized into eight types. To recognize Lampung characters, deep convolutional neural network (DCNN) architecture is proposed. The novelty of this architecture lies in optimizing document-based and handwritten character recognition to achieve the best performance in terms of accuracy and execution time. The proposed architecture will be compared to principal component analysis (PCA) combined with support vector machine (SVM) to evaluate its results. Experimental results using the DCNN architecture show an average accuracy of 99.3% and an execution time of 283 seconds for all data, while PCA and SVM exhibit an average accuracy of 92.9%. Furthermore, the recognition results for all data from documents and handwritten samples yield satisfactory accuracy of 98.6%. These results make the DCNN architecture suitable for use in recognizing Lampung characters and are expected to make it easier for Lampung people to recognize Lampung character.

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