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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 63 Documents
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Search results for , issue "Vol 10, No 5: October 2021" : 63 Documents clear
Goal location prediction based on deep learning using RGB-D camera Heba Hakim; Zaineb Alhakeem; Salah Al-Darraji
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3170

Abstract

In the navigation system, the desired destination position plays an essential role since the path planning algorithms takes a current location and goal location as inputs as well as the map of the surrounding environment. The generated path from path planning algorithm is used to guide a user to his final destination. This paper presents a proposed algorithm based on RGB-D camera to predict the goal coordinates in 2D occupancy grid map for visually impaired people navigation system. In recent years, deep learning methods have been used in many object detection tasks. So, the object detection method based on convolution neural network method is adopted in the proposed algorithm. The measuring distance between the current position of a sensor and the detected object depends on the depth data that is acquired from RGB-D camera. Both of the object detected coordinates and depth data has been integrated to get an accurate goal location in a 2D map. This proposed algorithm has been tested on various real-time scenarios. The experiments results indicate to the effectiveness of the proposed algorithm.
Teaching power system stabilizer and proportional-integral-derivative impacts on transient condition in synchronous generator Sugiarto Kadiman; Oni Yuliani; Trie Handayani
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3087

Abstract

Understanding the concepts based on problem solving is not an easy methodology in teaching the impact of power systems stabilizer (PSS) on transient synchronous generator using MATLAB capability. Experiments conducted in simulating sessions play an important role in this teaching. This simulation can simulate power system stability behavior with reasonable accuracy in less time. This transient phenomenon of a power system utilizing synchronous generator and modelling by fully three-phase model with changes in stator flux linkages neglected is analyzed by employed single machine infinite bus taken to the power system. Whereas a power system stabilizer which consist of a wash-out circuit, two stages of compensation, a filter unit, and a limiter, is applied to control voltage and frequency of power systems in transient condition. Proportional-integral-derivative (PID) controller tuned by Ziegler-Nichols’s method is cascaded to conventional PSS in order to enhance the response time of system while providing a better result in damping for oscillation. This gives the clear idea about PSS and PID controller impacts on transient synchronous generator and its enhancement to the students of electrical engineering program, Institut Teknologi Nasional Yogyakarta.
Analysis of thermal models to determine the loss of life of mineral oil immersed transformers Mohammad Tolou Askari; Mohammad Javad Mohammadi; Jagadeesh Pasupuleti; Mehrdad Tahmasebi; Shangari K. Raveendran; Mohd Zainal Abdin Ab Kadir
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3131

Abstract

Hot spot as well as top oil temperatures have played the most effective parameters on the life of the electrical transformers. The prognostication of these factors is very vital for determining the residual life of the electrical transformers in the transmission and distribution systems. Thus, an accurate mathematical method is required to calculate the critical temperature such as hot spot and top oil temperature based on the different types of thermal models. In this study calculates the service life of the transformers based on an accurate top oil temperature. Accordingly, An approach solution is given for calculating the thermal model. Also, findings are validated with true temperatures. Finally, this method is implemented on 2500 KVA electrical transformer.
A new design of stepped antenna loaded metamaterial for RFID applications Badr Nasiri; Ahmed Errkik; Jamal Zbitou
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2675

Abstract

Radio frequency identification is being overloaded with data information, making wideband band antennas very appealing. In this paper, we present a new design of dual band antenna for RFID reader applications operating at 2.45Gz and 5.8GHz with an average gain of 1.16dB at the lower frequency band and 3.2dB at the higher frequency band. The antenna is designed on an FR-4 substrate having a relative dielectric constant of 4.4 and loss tangent of 0.025. The proposed antenna is simulated, designed and, optimized using CST Microwave Studio and has a small size of 32 mm x 26 mm x 1.6 mm. The antenna consists of a steeped rectangular patch antenna using a partial ground plane loaded a modified split ring resonator. The metamaterial structure was designed and optimized to operate at 2.45GHz and its effective parameters was verified using the Nicolson-Ross Weir method. The performance of the proposed antenna is confirmed by another 3D electromagnetic solver HFSS.
E-customer loyalty in gamified trusted store platforms: a case study analysis in Iran Ehsan Hosseini; Mohammad Hossein Rezvani
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3165

Abstract

Customer satisfaction, trust, and loyalty are the three most fundamental elements of e-marketing. Previous researchers have noted that satisfaction is a key factor in commanding loyalty. However, the relationship between satisfaction, trust, and loyalty is strongly dependent on the type of platform provided by digital stores. On the other hand, gamification in E-businesses has grown rapidly in recent years. In this context, it is necessary to explore the effects of gamification on e-customer satisfaction and loyalty. In this paper, it is argued that customer satisfaction alone cannot inspire loyalty. Simply speaking, customers’ satisfaction with gamified services can lead to developing trust and, in turn, loyalty. This research also presents a thorough review of the effect of store-related motivational factors, such as gamification, on trust. These factors include moderator and mediator variables. The hypotheses of this study are considered in the context of one of the largest online retail stores in Iran which enjoys a large market share in the Middle East. To this end, Lawshe content validity ratio is utilized and expert opinions are applied to the proposed model. Evaluation results, obtained through the smartPLS, established the robustness of our modeling in terms of reliability analysis, significance level analysis, discriminant validity analysis, coefficient of determination, model fitting, and cross-validation.
Analyzing the relationship between information technology jobs advertised on-line and skills requirements using association rules Frederick F. Patacsil; Michael Acosta
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2590

Abstract

Online job vacancy sites have become an important source of information about the characteristics of labor market demand. It has become an avenue for job matching by both employers and employees and to study and analyze the labor market. This study proposed a methodology for identifying and analyzing skill-job relationships using frequency word occurrences of skills as a requirement of the job. It employed association rule mining which aims to discover frequent patterns, relationships among a set of items in the database. It collected published job vacancy data to IT job and skills requirements from various job portal websites. The proposed job skill requirements for specific I.T. jobs published online analyzing using the FP-growth algorithm of association rule provide a new dimension in labor market research. The study revealed that skill words are highly related to a certain job requirement. The results of the study could provide insights on the gap between the school acquired skills and actual IT industry skill needs and as the basis for curriculum enhancement and policy-making interventions by the Philippine government in its educational system.
Business process monitoring system in supporting information technology governance Lanto Ningrayati Amali; Muhammad Rifai Katili; Sitti Suhada; Tri Alfandra Labuga
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3147

Abstract

Information technology (IT) is essential in supporting an organization's business sustainability and growth, making it critically dependent on IT. Therefore, a focus on IT governance, consisting of leadership, organizational structure, and process ensuring that IT organization supports and expands the organizational strategies and goals is required. When the business supports the strategic significance of IT investment, the implementation of an IT strategy will lead to the adoption of an IT governance model. It will support and help the description of the benefit roles and responsibilities from IT systems and infrastructure. This paper aims to develop a business process monitoring system to support IT governance in improving user service and measuring organizational performance. The research method was the system development method with the Waterfall model. To measure the performance of the business process, the self-assessment method with performance matrix tools was applied. The study resulted in a business process monitoring system that can enhance the organization’s primary business process in services, supporting the said organization’s performance.
Image processing system using MATLAB-based analytics Gerald K. Ijemaru; Augustine O. Nwajana; Emmanuel U. Oleka; Richard I. Otuka; Isibor K. Ihianle; Solomon H. Ebenuwa; Emenike Raymond Obi
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.3160

Abstract

Owing to recent technological advancement, computers and other devices running several image editing applications can be further exploited for digital image processing operations. This paper evaluates various image processing techniques using matrix laboratory (MATLAB-based analytics). Compared to the conventional techniques, MATLAB gives several advantages for image processing. MATLAB-based technique provides easy debugging with extensive data analysis and visualization, easy implementation and algorithmic-testing without recompilation. Besides, MATLAB's computational codes can be enhanced and exploited to process and create simulations of both still and video images. Moreover, MATLAB codes are much concise compared to C++, thus making it easier for perusing and troubleshooting. MATLAB can handle errors prior to execution by proposing various ways to make the codes faster. The proposed technique enables advanced image processing operations such as image cropping/resizing, image denoising, blur removal, and image sharpening. The study aims at providing readers with the most recent MATLAB-based image processing application-tools. We also provide an empirical-based method using two-dimensional discrete cosine transform (2D-DCT) derived from its coefficients. Using the most recent algorithms running on MATLAB toolbox, we performed simulations to evaluate the performance of our proposed technique. The results largely present MATLAB as a veritable approach for image processing operations.
Automatic time series forecasting using nonlinear autoregressive neural network model with exogenous input Hermansah Hermansah; Dedi Rosadi; Abdurakhman Abdurakhman; Herni Utami
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2862

Abstract

This study aims to determine an automatic forecasting method of univariate time series, using the nonlinear autoregressive neural network model with exogenous input (NARX). In this automatic setting, users only need to supply the input of time series. Then, an automatic forecasting algorithm sets up the appropriate features, estimate the parameters in the model, and calculate forecasts, without the users’ intervention. The algorithm method used include preprocessing, tests for trends, and the application of first differences. The time series were tested for seasonality, and seasonal differences were obtained from a successful analysis. These series were also linearly scaled to [−1, +1]. The autoregressive lags and hidden neurons were further selected through the stepwise and optimization algorithms, respectively. The 20 NARX models were fitted with different random starting weights, and the forecasts were combined using the ensemble operator, in order to obtain the final product. This proposed method was applied to real data, and its performance was compared with several available automatic models in the literature. The forecasting accuracy was also measured by mean squared error (MSE) and mean absolute percent error (MAPE), and the results showed that the proposed method outperformed the other automatic models.
Levenberg-marquardt backpropagation neural network with techebycheve moments for face detection Ali Nadhim Razzaq; Rozaida Ghazali; Nidhal Khdhair El Abbadi; Hussein Ali Hussein Al Naffakh
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2364

Abstract

Face detection is an intelligent approach used in a variety of applications that identifies human faces in digital images. This work presents a new method which composes of a neural network and Techebycheve transforms for face detection. For feature extraction, Tchebychev transform was applied, in which a discrete Tchebychev transform is given for different sampling patterns and several samples here were performed on color images. A Levenberg-Marquardt backpropagation neural network was applied to the transformed image to find faces in the face detection dataset and FDDB benchmarked database. Model performance was measured based on its accuracy and the best result from the newly proposed method was 98.9%. Simulation results showed that the proposed method handles face detection efficiently.

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