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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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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.
A wearable device for machine learning based elderly's activity tracking and indoor location system Nour Eddin Tabbakha; Chee Pun Ooi; Wooi Haw Tan; Yi-Fei Tan
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2737

Abstract

The number of older people is increasing in many countries. By 2030, it is estimated that 15% of the overall population will be comprised of people aged 65 and above. Hence, the monitoring and tracking of elder activities to ensure they live an active life has become a major research topic in recent years. In this work, an elderly sub-activity tracking system is developed to detect the sub-activity of the elderly based on their physical activities and indoor location. The physical activities tracking system and indoor location system is combined in this project to enhance the context of the elderly activities (i.e. sub-activities as defined in this project). An indoor location system is developed by using Bluetooth Low Energy (BLE) beacon and BLE scanners to measure the Received Signal Strength Indicator (RSSI) signal to detect the location of the elderly. The activity tracking is carried out via a waist wearable device worn by the elderly. Random forest and Support Vector Machine (SVM) are used as machine learning classifiers to predict the activity and indoor location with an accuracy of 95.03% and 86.58%, respectively. The data from activity tracking and indoor location sub-systems will then be combined to derive the sub-activity and push to an online Internet of Things (IoT) platform for remote monitoring and notification.
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.
Threshold benchmarking for feature ranking techniques Ruchika Malhotra; Anjali Sharma
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2752

Abstract

In prediction modeling, the choice of features chosen from the original feature set is crucial for accuracy and model interpretability. Feature ranking techniques rank the features by its importance but there is no consensus on the number of features to be cut-off. Thus, it becomes important to identify a threshold value or range, so as to remove the redundant features. In this work, an empirical study is conducted for identification of the threshold benchmark for feature ranking algorithms. Experiments are conducted on Apache Click dataset with six popularly used ranker techniques and six machine learning techniques, to deduce a relationship between the total number of input features (N) to the threshold range. The area under the curve analysis shows that ≃ 33-50% of the features are necessary and sufficient to yield a reasonable performance measure, with a variance of 2%, in defect prediction models. Further, we also find that the log2(N) as the ranker threshold value represents the lower limit of the range.
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.
Examining a display-peeping prevention method that uses real-time UI part transparency linked to motion detection by video analysis Koki Kishibata; Masaki Narita
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.2565

Abstract

In recent years, the use of various information terminals such as smartphones and personal computers have become widespread, and situations where information terminals are used have become diverse. With increased opportunities to use information terminals outdoors and during travel, some users have been using peep-prevention filters, or software with an equivalent function, on their displays, in order to protect their privacy. However, such filters have problems with regards their effectiveness, ease of use, and the user being able recognize when they are vulnerable to peeping. Decrease in display visibility, unprotected angles, and the fact that it is difficult for users to notice when others are watching their screen, are some examples of such problems. Also, recently, many information terminals recently distributed have built-in cameras. In this paper, in order to solve the aforementioned problems, we propose to detect motion, video analyze , and transparentize part of the user interface (UI) in real time by using a laptop’s built-in camera. This method is enabled with low-load and can be applied to various terminals. Further, in order to verify the effectiveness of the method, we implemented a prototype, and carried out an evaluation experiment on experimental subjects. Results from the experiment confirmed that real-time UI transparentization is a very effective method for protecting privacy of information terminals.
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.
Design of an internet of things based real-time monitoring system for retired patients Vaclav Mach; Milan Adamek; Jiri Sevcik; Jan Valouch; Karla Barcova
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.2699

Abstract

The main aim of this article is to design a monitoring center for collecting and evaluating the physiological function of retired patients in nursing homes. The system should be able to collect the information of body heat, heart rate, blood oxygen, orientation, and sleep time in the form of the little bracelet. The evaluating part of the system with the program can be placed into personal computer (PC) which can provide a user-friendly interface and easy managing. The program can display all needed information of the patient from previous days or months in the form of the graphs and the nursing person can have the view of the patient´s physiological health. The evaluation and the collection of the data from each patient are done only on the card and the computer is only a device for live-view and managing. In case of the power failure, the monitoring system will be still operating normally due to the uninterruptible power supply (UPS) in the form of the battery. It means that the system will operate even if the PC is powered off. The system also has several external communication interfaces like wireless fidelity (Wi-Fi), ethernet, and general packet radio service (GPRS) which provides an external connection.
Identification of batik making method from images using convolutional neural network with limited amount of data Mohammad Arif Rasyidi; Ruktin Handayani; Fauzul Aziz
Bulletin of Electrical Engineering and Informatics Vol 10, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i3.3035

Abstract

This study aims to apply the convolutional neural network (CNN) to classify batik based on its manufacturing method, namely Batik Tulis which are hand drawn, Batik Cap where stamps are used to create the pattern, and Batik Printing which are printed using textile printing machine. We collected 40 images for each type of batik with a total of 120 images. To speed up and simplify the model building process, we implemented transfer learning with 3 basic CNN model architectures, namely ResNet, DenseNet, and VGG with batch normalization. We also experimented with building a new dataset by breaking each image down into 30 smaller images. Image augmentation was also used to prevent overfitting as well as to provide variations in the training data. The experimental results with 5-fold cross validation show that densenet169 gives the best results on the original dataset with an accuracy of 79.17% while vgg13_bn shows the best performance on the modified dataset with an accuracy of 87.61%. All models showed an increase in performance when using the modified dataset, except densenet169 which did not show a significant difference in performance.

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