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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 4: August 2021" : 63 Documents clear
An efficient and improved model for power theft detection in Pakistan Abid Afridi; Abdul Wahab; Shamsher Khan; Wasi Ullah; Sheharyar Khan; Syed Zia Ul Islam; Kashif Hussain
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.3014

Abstract

This paper describes an improved model for the monitoring of power used by a party such as household users and different industries in Pakistan. The power theft detection was done using the intelligent internet of things (IoT) service system for calculating the user's power simultaneously. The power meter catches a theft detection device that is instantly transmitted to the central system which compares both the data by means of microcontroller and if there is any difference found, it informs the power utility about the hooking, meter relief or theft activities happen. Information of the theft detection through the global mobile communications system is transmitted and notified theft is displayed on the terminal monitor or won. As a result, although consumers continue to use excess fuel, the customer's power supply is cut in the electricity boards segment. The general radio package module system sends central circuit and meter data via an internet protocol address to a web server. GSM's IoT based perception is used to monitor the power supply and billing information calculated with a microcontroller continuously with the determination of the electricity table area. With this unit, the duplicate user can be located at the rear of the electricity office with the power meter status.
Optimal setting of DOC relay in distribution system in presence of D-FACTS Lazhar Bougouff; Abdelaziz Chaghi
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2809

Abstract

The process of selecting optimal settings for directional over-current relays (DOC relays) is a selection of time dial setting (TDS) and IP (backup current), So that changes in the system of electrical power distribution. In this work, a breeder genetic algorithm (BGA) has been applied to optimal settings of DOC relays with multisystem D-FACTS devices. The simulation consists of two network operation scenarios, scenario without D-FACTS which consisting of coordination of DOC relays against three phase faults, and the second scenarios with multi TCSC. In general, had been verified on optimal settings of relays that the impacts of TCSC insertion in 33-bus distribution system on DOC relays.
5G cognitive radio system design with new algorithm asynchronous spectrum sensing Mohammed Mehdi Saleh; Ahmed A. Abbas; Ahmed Hammoodi
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2839

Abstract

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.
Modified Blowfish algorithm analysis using derivation cases Theda Flare Ginoy Quilala; Rogel L. Quilala
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2292

Abstract

This study analyzed and enhanced the modified Blowfish algorithm (MBA) encryption. The modification retained the original structure, process and the use of two S-boxes in the MBA but presented two derivation processes in the f-function which was originally placed to prevent symmetry. The derivation case’s performance was analyzed using avalanche effect and time efficiency. After comparing the first and second derivation process presented in the MBA, the second derivation further improved the avalanche effect by 5.47%, thus improving security. The performance also showed that the second modification is faster by 39.48% in encryption time, and 38.34% faster in decryption time. The first derivation case in the modified Blowfish was slower in time because of the difference in the placement of the shift rotation. The key generation time was found to be independent of the input size while the encryption and decryption time was found to be directly proportional to file size. With this, the second modification is considered to be better.
UI/UX integrated holistic monitoring of PAUD using the TCSD method Erly Krisnanik; Tri Rahayu
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.3108

Abstract

User interface (UI)/user experience (UX) is one part of the stages in the development of the system to produce interactive and attractive web-based application layouts so that it is easy to understand and use by users. In this research, a case study was conducted on early childhood in PAUD Kuntum Mekar. The design of the UI/UX model for holistic integrative PAUD monitoring becomes one of the solutions to help parents and teachers. The method used to design UI/UX is the task centered system design (TCSD) approach starting from the stages; 1) identification scope of use, 2) user centered requirement analysis, 3) design and scenario, and 4) walkthrough evaluate, the method used for system testing is user satisfaction, and heuristic usability. The purpose of this study is the UI/UX design with TCSD can provide valid data needs of each actor based on the assignment and design of the story board of the developed system. The results of this research are UI/UX model design for integrative holistic PAUD monitoring application.
Triple-layer remote phosphor structure: a selection of the higher color quality and lumen efficiency for WLEDs Phan Xuan Le; Le Hung Tien
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.3084

Abstract

To enhance color quality of glass-based phosphor-converted white light-emitting diodes (pc-WLEDs) with multi-layer remote phosphor layer structures, two phosphors, green CdS:In and red ZnS:Te,Mn, are integrated into the glass matrix and applied to the dual-layer and triple-layer WLED packages. The attained results were examined with Mie-scattering theory and Lambert-Beer law. The dual-layer showed significant enhancement in color rendering index (CRI), in the range of approximate 80-90. Meanwhile, CRI in the triple-layer was lower and stayed around 66. In terms of color quality scale (CQS), a more overall color evaluating index, triple-layer structure helps the glass-based WLED achieve higher value than the dual-layer. The triple-layer is also beneficial to the luminous efficacy, according to the experimented results. Thus, the triple-layer structure can be used to strengthen the benefit of the glass matrix used in WLED products.
Hoax analyzer for Indonesian news using RNNs with fasttext and glove embeddings Ryan Adipradana; Bagas Pradipabista Nayoga; Ryan Suryadi; Derwin Suhartono
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2956

Abstract

Misinformation has become an innocuous yet potentially harmful problem ever since the development of internet. Numbers of efforts are done to prevent the consumption of misinformation, including the use of artificial intelligence (AI), mainly natural language processing (NLP). Unfortunately, most of natural language processing use English as its linguistic approach since English is a high resource language. On the contrary, Indonesia language is considered a low resource language thus the amount of effort to diminish consumption of misinformation is low compared to English-based natural language processing. This experiment is intended to compare fastText and GloVe embeddings for four deep neural networks (DNN) models: long short-term memory (LSTM), bidirectional long short-term memory (BI-LSTM), gated recurrent unit (GRU) and bidirectional gated recurrent unit (BI-GRU) in terms of metrics score when classifying news between three classes: fake, valid, and satire. The latter results show that fastText embedding is better than GloVe embedding in supervised text classification, along with BI-GRU + fastText yielding the best result.
The influence of data size on a high-performance computing memetic algorithm in fingerprint dataset Priati Assiroj; Harco Leslie Hendric Spits Warnars; Edi Abdurachman; Achmad Imam Kistijantoro; Antoine Doucet
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2760

Abstract

The fingerprint is one kind of biometric. This biometric unique data have to be processed well and secure. The problem gets more complicated as data grows. This work is conducted to process image fingerprint data with a memetic algorithm, a simple and reliable algorithm. In order to achieve the best result, we run this algorithm in a parallel environment by utilizing a multi-thread feature of the processor. We propose a high-performance computing memetic algorithm (HPCMA) to process a 7200 image fingerprint dataset which is divided into fifteen specimens based on its characteristics based on the image specification to get the detail of each image. A combination of each specimen generates a new data variation. This algorithm runs in two different operating systems, Windows 7 and Windows 10 then we measure the influence of data size on processing time, speed up, and efficiency of HPCMA with simple linear regression. The result shows data size is very influencing to processing time more than 90%, to speed up more than 30%, and to efficiency more than 19%.
Impact of nonintrusive load monitoring on CO2 emissions in Malaysia Keh-Kim Kee; Yun Seng Lim; Jianhui Wong; Kein Huat Chua
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2979

Abstract

Nonintrusive load monitoring (NILM) based energy efficiency can conserve electricity by creating awareness with the behaviour change and shrinking CO2 emissions to the environment. However, the lack of effective models and strategies is problematic for policymakers to forecast quantitatively CO2 emissions. This paper aims to study the impact of NILM on CO2 emissions in Malaysia. Firstly, the predictive models were established based on Malaysia open data from 1996 to 2018. After that, scenario simulations were conducted to predict CO2 emissions and NILM impact on environmental degradation in 2019-2030. The results revealed that a 12% reduction in electricity consumption due to NILM could contribute to a 10.2% shrinkage of the total CO2 emissions. The result also statistically confirmed Malaysia to achieve a 45% reduction of CO2 intensity in 2030. With NILM, the carbon reduction can be further enhanced to 60.2%. The outcomes provide valuable references and supporting evidence for policymakers in planning effective carbon emission control policies and energy efficiency measures. The work can be extended by developing a decision support system and user interfaces access via the cloud.
Determining patterns of student graduation using a bi-level learning framework Lalida Nanglae; Natthakan Iam-On; Tossapon Boongoen; Komkrit Kaewchay; James Mullaney
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2502

Abstract

The practice of data science, artificial intelligence (AI) in general, has expanded greatly in terms of both theoretical and application domains. Many existing and new problems have been tackled using different reasoning and learning methods. These include the research subject, generally referred to as education data mining (or EDM). Among many issues that have been studied in this EMD community, student performance and achievement provide an interesting, yet useful result to shaping effective learning style and academic consultation. Specific to this work at Mae Fah Luang University, the pattern of students’ graduation is determined based on their profile of performance in different categories of courses. This course-group approach is picked up to generalize the framework for various undergraduation programmes. In that, a bi-level learning method is proposed in order to predict the length of study before graduation. At the first tier, clustering is applied to derive major types of performance profiles, for which classification models can be developed to refine the prediction further. With the experiments on a real data collection, this framework usually provides accurate predictive outcomes, using several conventional classification techniques.

Page 4 of 7 | Total Record : 63

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