cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
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 65 Documents
 1   2   3   4   5 
Search results for , issue "Vol 12, No 4: August 2023" : 65 Documents clear
Incorrect facemask-wearing detection using image processing and deep learning Zeyad Qasim Habeeb; Imad Al-Zaydi
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4786

Abstract

Now and in the future, a face mask is a very important strategy to protect people when a new contagious life threatens disease spread through the air appears. Currently, there is a serious health emergency because of the coronavirus disease 2019 (COVID-19) epidemic. The negative consequences of this pandemic need to be protected in public areas. Numerous methods are advised by the World Health Organization (WHO) to reduce infection rates and prevent depleting the available medical resources in the absence of efficient antivirals. Wearing masks is a non-pharmaceutical strategy to lessen the susceptibility to COVID-19 infection. This research aims to create a face mask identification system that is efficient and uses deep learning, which has proven to be beneficial in many real-world applications. This system has also used a transfer learning method with the MobileNetV2 model to classify people who wear face masks properly, wear face masks improperly, and are without masks. The results demonstrate that the proposed system has an accuracy of 99.4% which is higher than current systems.
Performance analysis of wireless power transfer using series-to-series topology Fairul Azhar Abdul Shukor; Ahmed Mohammed Salem Ahmed Alhattami; Nur Ashikin Mohd Nasir; Chockalingam Aravind Vaithilingam
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4834

Abstract

Wireless power transfer (WPT) is a technology used to transmit power using air as it medium of transfer. The function of the WPT is similar to a transformer. The power provided on the primary side will be transferred through air to the secondary side. The performance of the WPT is crucially depends on the air gap length, ???? that separates primary and secondary side. In this paper discusses the performance of WPT using series-to-series topology. The performance of the WPT was estimated using finite element analysis (FEA). During the study, focus was given to effect of turn ratio, a, air gap length, ???? and capacitor value at primary Cp, and secondary, Cs winding to voltage ratio of the WPT. The air gap length, ???? was set to 1 and 2 mm while the capacitors were set depend on the ratio of primary to secondary winding capacitor, Cp/Cs. The WPT performance also being tested under no-load and loaded operation to observed it effect. As a result, the WPT with turn ratio, a at 0.37, air gap length, ???? at 1 mm and ratio of primary to secondary winding capacitor, Cp/Cs at 0.5 produce the best voltage ratio compared to other settings.
Reactive power planning with the help of multi-objective genetic algorithm and flexible AC transmission systems devices Prince Hooda; Mukesh Kumar Saini
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.5229

Abstract

In this paper power quality of 3-bus solar-based hybrid system has been presented (where one or more than one distribution generator unit is connected to the grid). The injection of solar power into grid-connected systems creates power quality problems such as current consistency, electrical fluctuations, and inefficient power demand. A power quality control strategy based on a real-time self-regulation method for autonomous microgrid operation has been presented. In this paper solar farm design and satisfactory performance tests such as PV-static synchronous compensator (STATCOM) to improve the power quality of grid-based systems have been presented using the MATLAB/Simulink environment. Pulse width modulator (PWM) with proportional-integral derivative (PID) controller used for frequency control, reactive var compensation is used to control voltage profile. Multi-objective genetic algorithm (MOGA) for reactive power planning (RPP) with the objective of reactive power minimization is introduced. The optimization variables are generator voltage, transformer tap changer, and various operational constraints.
Hash algorithm comparison through a PIC32 microcontroller Asmae Zniti; Nabih El Ouazzani
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4982

Abstract

This paper presents a comparative study involving SHA-3 final round candidates along with recent versions of hash algorithms. The proposed comparison between hash functions is performed with respect to cycles per byte and memory space. Tests are also carried out on a PIC32-based application taking into account several input cases, thus resulting in a set of ranked algorithms in terms of their specified metrics. The outcome of this work represents a considerable contribution in data protection and information security in relation to various communication and transmission systems, serving as a handy reference for developers to select an appropriate hash algorithm for their particular use condition.
Sentiment analysis from Bangladeshi food delivery startup based on user reviews using machine learning and deep learning Abu Kowshir Bitto; Md. Hasan Imam Bijoy; Md. Shohel Arman; Imran Mahmud; Aka Das; Joy Majumder
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4135

Abstract

Food delivery methods are at the top of the list in today's world. People's attitudes toward food delivery systems are usually influenced by food quality and delivery time. We did a sentiment analysis of consumer comments on the Facebook pages of Food Panda, HungryNaki, Pathao Food, and Shohoz Food, and data was acquired from these four sites’ remarks. In natural language processing (NLP) task, before the model was implemented, we went through a rigorous data pre-processing process that included stages like adding contractions, removing stop words, tokenizing, and more. Four supervised classification techniques are used: extreme gradient boosting (XGB), random forest classifier (RFC), decision tree classifier (DTC), and multi nominal Naive Bayes (MNB). Three deep learning (DL) models are used: convolutional neural network (CNN), long term short memory (LSTM), and recurrent neural network (RNN). The XGB model exceeds all four machine learning (ML) algorithms with an accuracy of 89.64%. LSTM has the highest accuracy rate of the three DL algorithms, with an accuracy of 91.07%. Among ML and DL models, LSTM DL takes the lead to predict the sentiment.
Performance evaluation of microgrid with extreme learning machine based PID controller Isha Rajput; Jyoti Verma; Hemant Ahuja
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4029

Abstract

The enhanced penetration of the renewable energy sources (RES) is dependent on microgrid (MG) to a power system is impact stability of the system due to a variation in dynamic properties of the MG from a traditional generator. As a result, analyzing the new issues with dynamic stability and controlling the operation of the power system in the connection of rising MG penetration becomes critical. This paper contains a MG system with renewable energy assisted, superconducting magnetic energy storage (SMES) storage and an extreme learning machine (ELM) based proportional integral derivative (PID) controller. The effect of renewable-based MG penetration on a dynamic stability and control of the multi machine multi area system under varied operating situations is comprehensively investigated in this study. Non-linear time-domain simulations and several performance indicators are used to evaluate the controller's ability with the different MG penetration percentages under various disturbances and operational conditions.
Distributed formation control for groups of mobile robots using consensus algorithm Ryandika Afdila; Fahmi Fahmi; Arman Sani
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.3869

Abstract

The increasing implementation of autonomous robots in industries and daily life demands the development of a robust control algorithm that enables robots to perform their tasks successfully. Critical tasks such as rescue missions and area exploration require robots to work cooperatively in a formation to accomplish the tasks quickly. Moreover, the existence of obstacles in the environment requires all the robots' to rapidly process environmental changes to maintain the formation pattern. Thus, this paper introduces a distributed robot formation control system using the consensus algorithm that enables a group of robots to establish and maintain formations using only the local information of the robots. Furthermore, an obstacle avoidance algorithm based on the distance and angle between robots and obstacles is introduced to ensure safe navigation for the group of robots. The algorithm's effectiveness is demonstrated by a multi-robot system with randomly generated starting positions and velocities, where it is shown that the robots can agree on the control variables and establish the required formation while also avoiding obstacles in the environment.
A proposed approach to discover nearest users on social media networks based on users' profiles and preferences Mahmood Shakir Hammoodi; Ahmed Al-Azawei
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4436

Abstract

Social media sites (SMSs) become essential platforms used by people, customers, and companies for communication and marketing. Social media networks (SMNs) allow access to individuals who share their information and this, in turn, can lead to build users' profiles. Profiles can consist of a basic description of users' characteristics such as name, age, gender, education, marital status, email, phone number, and location. Preferences, on the other side, describe users' behavior on SMNs. Earlier literature defined a user's identity in different networks based on matching his/her name only. This research, however, proposes an integrated approach for discovering the nearest users by considering profiles and preferences. The proposed approach includes three key steps. First, users are grouped based on their preferences such as personal interests. Second, properties’ values of a user profile and preferences are integrated to identify the nearest users. Finally, the nearest users to a certain user are identified by measuring the boundary distance. The findings show that the proposed approach can effectively identify the nearest users. Comparing the performance of the proposed approach with the two highly adopted approaches that rely on either users' profiles or preferences suggests that the proposed approach in this research is less prone to error.
Design and manufacture control system for water quality based on IoT technology for aquaculture in the Vietnam Tran Duc Chuyen; Dien Duc Nguyen; Nguyen Cao Cuong; Vu Viet Thong
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.5180

Abstract

In this paper, presents solutions to apply internet of things (IoT) technology in the field of high-tech agriculture and aquaculture in coastal areas of Vietnam, which is currently a new problem. The system includes an application on a smartphone; access parameters via the web, a computer and an IoT control circuit capable of automatically drawing electricity from the solar panel to the energy storage to serve as a source of power for devices (monitoring cabinets). The product has the function of monitoring: water environmental indicators in shrimp ponds (temperature, pH, dissolved oxygen (DO), salinity, redox index at the bottom of oxygen reduction potential (ORP)), on the website 24/24h, and controllable. Automatic control of pump system and DO generator with Inverter technology. The research results in this paper have brought high economic benefits with an automatic water quality control system to improve the productivity and quality of shrimp farming in practice for people in the aquaculture area in Bach Long commune, Giao Thuy district, Nam Dinh province, Vietnam.
Malaysia coin identification app using deep learning model Dania Qistina Mohd Nazly; Pradeep Isawasan; Khairulliza Ahmad Salleh; Savita K. Sugathan
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4601

Abstract

Most of the human work has been replaced by computers in recent years. With the rise of mobile technology and Internet access, recent developments in machine learning (ML) have designed many algorithms to solve diverse human problems. However, due to a lack of exposure to image processing, identification technology is still not widely employed in Malaysia. This paper outlines the steps involved in creating a mobile application for coin identification using ML. In the literature review, the history of the coins is studied in more depth and the features of already existing coin identification mobile applications are compared by their advantages and disadvantages. In addition, using the neural network model, the classification accuracy of successfully identified coins is recorded and disclosed. This study includes the limitations of the prototype mobile application and future improvements that could be added.

Page 2 of 7 | Total Record : 65

 1   2   3   4   5 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol 14, No 6: December 2025 Vol 14, No 5: October 2025 Vol 14, No 4: August 2025 Vol 14, No 3: June 2025 Vol 14, No 2: April 2025 Vol 14, No 1: February 2025 Vol 13, No 6: December 2024 Vol 13, No 5: October 2024 Vol 13, No 4: August 2024 Vol 13, No 3: June 2024 Vol 13, No 2: April 2024 Vol 13, No 1: February 2024 Vol 12, No 6: December 2023 Vol 12, No 5: October 2023 Vol 12, No 4: August 2023 Vol 12, No 3: June 2023 Vol 12, No 2: April 2023 Vol 12, No 1: February 2023 Vol 11, No 6: December 2022 Vol 11, No 5: October 2022 Vol 11, No 4: August 2022 Vol 11, No 3: June 2022 Vol 11, No 2: April 2022 Vol 11, No 1: February 2022 Vol 10, No 6: December 2021 Vol 10, No 5: October 2021 Vol 10, No 4: August 2021 Vol 10, No 3: June 2021 Vol 10, No 2: April 2021 Vol 10, No 1: February 2021 Vol 9, No 6: December 2020 Vol 9, No 5: October 2020 Vol 9, No 4: August 2020 Vol 9, No 3: June 2020 Vol 9, No 2: April 2020 Vol 9, No 1: February 2020 Vol 8, No 4: December 2019 Vol 8, No 3: September 2019 Vol 8, No 2: June 2019 Vol 8, No 1: March 2019 Vol 7, No 4: December 2018 Vol 7, No 3: September 2018 Vol 7, No 2: June 2018 Vol 7, No 1: March 2018 Vol 6, No 4: December 2017 Vol 6, No 3: September 2017 Vol 6, No 2: June 2017 Vol 6, No 1: March 2017 Vol 5, No 4: December 2016 Vol 5, No 3: September 2016 Vol 5, No 2: June 2016 Vol 5, No 1: March 2016 Vol 4, No 4: December 2015 Vol 4, No 3: September 2015 Vol 4, No 2: June 2015 Vol 4, No 1: March 2015 Vol 3, No 4: December 2014 Vol 3, No 3: September 2014 Vol 3, No 2: June 2014 Vol 3, No 1: March 2014 Vol 2, No 4: December 2013 Vol 2, No 3: September 2013 Vol 2, No 2: June 2013 Vol 2, No 1: March 2013 Vol 1, No 4: December 2012 Vol 1, No 3: September 2012 Vol 1, No 2: June 2012 Vol 1, No 1: March 2012 List of Accepted Papers (with minor revisions) More Issue