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 2,901 Documents
 214   215   216   217   218 
System interactive reader using eye-tracker technology in ebook reader Sujaini, Herry; Safriadi, Novi; Khairiyah, Dian
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.v13i3.5877

Abstract

Interest in using ebooks by the academic community is very high. Still, there is a problem when readers are reading through screens, tend to read fast, only scan the necessary parts, and don't focus on paying attention to the content they read, so this reduces the quality of reading because readers don't study the overall meaning of the sentence. Hence, this research aims to build an interactive reader system by integrating eye tracker technology with a webcam which is expected to solve the problem of decreasing the quality of reading through the screen by helping readers stay focused on their reading and providing an interactive system that makes it easier for readers to control the computer while reading. This research adopts the waterfall method and is divided into six stages. The system is designed using class diagrams, use case diagrams, and activity diagrams. Also, the system is built using the Python language with the Django framework. Then, the interactive reader system was tested using black box testing and usability testing methods. Based on the test results, it is shown that the interactive reader system that was built can help improve the quality and concentration when reading activities take place.
Novel entropy-based style transfer of the object in the content image using deep learning Raghatwan, Jyoti Sudhakar; Arora, Sandhya
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.v13i5.7659

Abstract

Recently neural style transfer (NST) has drawn a lot of interest of researchers, with notable advancements in color representation, texture, speed, and image quality. While previous studies focused on transferring artistic style across entire content images, a new approach proposes to transfer style specifically to objects within the content image based on the style image and maintain photorealism. Recent techniques have produced intriguing creative effects, but often only work with artificial effects, leaving real flaws visible in photographs used as references for styles. The suggested approach employs a two-dimensional wavelet transform (WT) to achieve style transfer by adjusting image structure with high-pass and low pass filters (LPF). Preserving the information content and numerical attributes of VGGNet19 through WT-based style transfer using the db5 WT at level 5, we can achieve a peak signal-to-noise ratio (PSNR) value of up to 96.76725. The qualitative result of the proposed methodology is compared with other existing algorithm. Also, the time complexity of the proposed methodology on different hardware platforms has been calculated and presented in the paper. The proposed methodology able to maintains appealing and precise quality of resultant image.
Dual-band GPS/LoRa antenna for internet of thing applications Yahya, Muhammad Sani; Soeung, Socheatra; Emmanuel Chinda, Francis; Musa, Umar; Yunusa, Zainab
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6428

Abstract

This paper presents the design and characterization of a compact dual-band microstrip antenna for GPS and long range (LoRa) internet of thing (IoT) applications. The antenna operates at 868 MHz and 1.57 GHz and has a gain of 3.35 dBi and 5.08 dBi, respectively. The antenna design is optimized using CST microwave studio software (MWS®), and both simulation and measurement results are in close agreement. The antenna features a directional E-plane and omnidirectional H-plane radiation pattern in each band of operation. The proposed antenna’s compact size and dual-band capability make it suitable for IoT applications that require GPS and LoRa communication in a small form factor. The results presented in this paper demonstrate the feasibility and effectiveness of the proposed antenna design.
Smart irrigation with crop recommendation using machine learning approach Palakshappa, Anitha; Kyathanahalli Nanjappa, Sowmya; Mahadevappa, Punitha; Sinchana, Sinchana
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.v13i3.6103

Abstract

Increasing crop yield with sustainable growth is the primary requirement for farmers with a growing population. Effective management and conservation of depleting natural resources is a priority task. Decrease in manpower due to migrating population has forced automation in agriculture. In this work, an automatic water irrigation and an effective crop recommendation system is proposed. Gypsum blocks based soil sensor is used to measure dielectric permittivity associated with the tested soil. The water-potential present in soil, along with potassium (K), nitrogen (N), phosphorus (P), potential of hydrogen (pH) helps to quantify the soil nutrients available and the suitable crop that can be considered for harvesting in a specified demography and environment. Sensory data indicating soil quality obtained is used to recommend crops by utilizing machine learning approaches. Telegram application is linked to the recommendation model to assist decision making and to ensure farmer-friendliness by sending notifications periodically.
Optimal control of automatic voltage regulator system using hybrid PSO-GWO algorithm-based PID controller Bouaddi, Abdessamade; Rabeh, Reda; Ferfra, Mohammed
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.v13i5.8186

Abstract

In this paper, a new hybrid optimization algorithm known as particle swarm optimization and grey wolf optimizer (PSO-GWO) based proportional integral derivative (PID) controller is suggested for automatic voltage regulator (AVR) system terminal tracking problem. The main objective of the suggested approach is to reduce crucial performance factors such as rise time, settling time, peak overshoot and peak time of the voltage of the power system in order to improve the AVR system's transient response. This analysis was compared to results obtained from existing heuristic algorithm-based approaches found in the literature, proving the improved PID controller's enhanced performance obtained through the suggested approach. Furthermore, the performance of the tuned controller with respect to disturbance rejection and its robustness to parametric uncertainties were evaluated separately and compared with existing control approaches. According to the obtained comparison results and from all simulations, using MATLAB-Simulink tool, it has been noted that the PID controller optimized using PSO-GWO algorithm has superior control performance compared to PID controllers tuned by ABC, DE, BBO and PSO algorithms. The main conclusion of the presented study highlights that the recommended strategy can be effectively implemented to improve the performance of the AVR system.
An optimistic-pessimistic game cross-efficiency method based on a Gibbs entropy model for ranking decision making units Thongmual, Noppakun; Laoha, Chanchai; Wichapa, Narong
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.5747

Abstract

The game cross-efficiency method, a commonly utilized approach for ranking decision-making units in tie-breaking scenarios, is based on secondary goals. However, in certain data envelopment analysis ranking problems, the classical game cross-efficiency method may fail to differentiate all decision-making units effectively. To address this limitation, it is prudent to explore the development of a new method that can enhance the ranking performance of the classical game cross-efficiency approach. In this study, we propose a novel Gibbs entropy linear programming model that integrates both optimistic and pessimistic perspectives of the classical game cross-efficiency method for data envelopment analysis ranking problems. To validate the reliability and utility of our proposed method, we present three examples: the six nursing homes problem, numerical example 2, and an application involving twenty Thai provinces with cash crop data. The reliability of the proposed method is assessed using Spearman’s correlation coefficient (rs) on the numerical examples. The results demonstrate that the rs values for both the proposed method and the classical game crossefficiency method, specifically for the six nursing homes problem, numerical example 2, and the application involving twenty Thai provinces, are determined to be rs=0.998, 0.998, and 0.986 respectively.
MCDM-AHP and ELECTRE collaboration apps for the best vendor selection technique Akmaludin, Akmaludin; Samudi, Samudi; Baidawi, Taufik; Dalis, Sopiyan; Suriyanto, Adhi Dharma; Widianto, Kudiantoro
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.v13i4.7545

Abstract

Vendor selection techniques are very important to maintain supply chain services, optimal service creates strong consistency in maintaining the continuity of supply chain business processes. The aim of this research is to provide an objective and consistent understanding of the best techniques in vendor selection which are implemented openly through the collaboration of multi-criteria decision making-analytic hierarchy process (MCDM-AHP) and ELECTRE. Empirical studies show how this approach is able to provide optimal decision-making support for the vendor selection process. Eight criteria are required which have contradictory meanings in their apps. These criteria include quality of goods (QG), payment methods (PMs), payment terms (PTs), minimum transactions (MTs), discounts (DS), delivery times (DTs), inventory (IN), and service (SV). The comparison importance value of the criteria is used as a measure of weighting the criteria through two testing approaches, namely mathematical algebra matrices and expert choice apps, through accurately assessing the optimal eigenvector from the two test approaches. Decision making support was carried out by comparison using 342 preference matrices which were developed into concordance and discordance matrices, the elimination process with threshold matrices found that the ranking results of four vendors were ranked first as worthy of being a selection priority and fifteen other vendors were ranked below.
Zinc oxide-coated fiber-optic sensors for monitoring of edible oil adulteration with internet of things integration Haroon, Hazura; Othman, Siti Khadijah Idris@; Razak, Hanim Abdul; Zain, Anis Suhaila Mohd; Salehuddin, Fauziyah; Mukhtar, Wan Maisarah
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.v13i6.7604

Abstract

The study proposes a novel approach for detecting adulteration in edible oils utilising a zinc oxide (ZnO)-coated optical sensor. The procedure included the development of a sensor probe using a plastic optical fiber (POF) with a ZnO nanolayer deposition. The ZnO nanorods were applied to the surface of the POF via a hydrothermal process. The sensitivity and accuracy of uncoated and ZnO-coated POFs were compared, and it was discovered that the ZnO-coated POF was more sensitive to changes in the refractive index of the samples under testing. The study ascertained a correlation between the optical power and voltage of the sensor and the refractive index of the medium. As the adulterant concentration in the oil mixture increased, the refractive index of the medium altered. As a result, both the sensor’s output voltage and optical power decreased. Upon completion, it was discovered that the uncoated POF had a sensitivity of 0.073 V/%, whereas the ZnO-coated POF had a sensitivity of 0.085 V/%. These findings highlight the effectiveness of ZnO-coated optical sensors, as well as their potential integration into internet of things (IoT) platforms for monitoring adulteration in edible oils.
Performance evaluation of generative adversarial networks for generating mugshot images from text description Bahrum, Nur Nabilah; Setumin, Samsul; Othman, Nor Azlan; Fitri Maruzuki, Mohd Ikmal; Abdullah, Mohd Firdaus; Che Ani, Adi Izhar
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.v13i1.5895

Abstract

The process of identifying photos from a sketch has been explored by many researchers, and the performance of the identification process is almost perfect, particularly for viewed sketches. Suspect identification based on sketches is one of the applications in forensic science. To identify the suspect using these kinds of methods, a face sketch is required. Hence, the methods require skilled artists to sketch the suspect based on descriptions provided by eyewitnesses. However, the skills of these artists are different from one another, which results in different rendered sketches. Therefore, this work attempts to propose a new identification method based only on forensic face-written descriptions. To investigate the feasibility of the proposed method, this study has evaluated the performance of some text-to-photo generators on both viewed and forensic datasets using three different models of GAN which are SAGAN, DFGAN, and DCGAN. Then, the generated images are compared to the real photo contained within those datasets to evaluate how well the proposed method recognizes the faces. The results demonstrated that the recognition rate for the generated photos by the DCGAN models is better than the other two models which achieve a 38.3% recognition rate at rank-10 for mugshot identification.
Performance evaluation of feature selections on some ML approaches for diagnosing the narcissistic personality disorder Sulistiani, Heni; Syarif, Admi; Muludi, Kurnia; Warsito, Warsito
Bulletin of Electrical Engineering and Informatics Vol 13, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i2.6717

Abstract

Narcissistic personality disorder (NPD) is a personality disorder that affects various aspects of life, including relationships, employment, school, and finances. Persons with NPD usually feel unhappy and disappointed when no one helps them and is not praised for their achievements. Diagnosing narcissism is generally done using a screening test that consumes time and costs a lot. This research aims to evaluate the performance of several feature selection (FS) approaches on machine learning (ML) techniques (support vector machine (SVM), random forest classifier (RFC), and Naive Bayes). Three scenarios of FS (all features, the information gain technique and the gain ratio (GR) feature technique) are used for each ML method. Several experiments using the benchmark narcissistic disorder dataset have been done. It adopts the k-fold cross-validation (10-fold cross-validation) strategy. We evaluate the method’s performance by measuring its accuracy, error rate, and processing time. It is shown that the RFC GR strategy gives the best performance with an accuracy of 100%.

Page 216 of 291 | Total Record : 2901

 214   215   216   217   218 

Filter by Year

2012 2025


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