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Bulletin of Electrical Engineering and Informatics
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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.
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Articles 52 Documents
Search results for , issue "Vol 9, No 4: August 2020" : 52 Documents clear
Multi-wavelet level comparison on compressive sensing for MRI image reconstruction Indrarini Dyah Irawati; Sugondo Hadiyoso; Yuli Sun Hariyani
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (771.477 KB) | DOI: 10.11591/eei.v9i4.2347

Abstract

In this study, weproposed compressive sampling for MRI reconstruction based on sparse representation using multi-wavelet transformation. Comparing the performance of wavelet decomposition level, which are level 1, level 2, level 3, and level 4. We used gaussian random process to generate measurement matrix. The algorithm used to reconstruct the image is l_1 norm. The experimental results showed that the use of wavelet multi-level can generate higher compression ratio but requires a longer processing time. MRI reconstruction results based on the parameters of the peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) show that the higher the level of decomposition in wavelets, the value of both decreases.
Machinery signal separation using non-negative matrix factorization with real mixing Anindita Adikaputri Vinaya; Sefri Yulianto; Qurrotin A’yunina Maulida Okta Arifianti; Dhany Arifianto; Aulia Siti Aisjah
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1158.758 KB) | DOI: 10.11591/eei.v9i4.1956

Abstract

A big challenge in detecting damage occurs when the sound of a machine mixes with the sound of another machine. This paper proposes the separation of mixed acoustic signals using Non-negative Matrix Factorization (NMF) method for fault diagnosis. The NMF method is an effective solution for finding hidden parameters when the number of observations obtained by the sensor is less than the number of sources. The real mixing process is done by placing two microphones in front of the machine. Two microphones will be used as sensors to capture a mixture of four machinery signals. Performance testing of signal separation is done by comparing baseline signals with estimated signals through the mean log spectral distance (LSD) and the mean square error (MSE). The smallest spectral distance between the estimated signal and the baseline signal is found in Ŝ2 with an average LSD of 1.26. The estimated signal Ŝ2 is the closest to the baseline signal with MSE of 1.15 x 10-2. The pattern of bearing damage in the male screw compressor can be identified from the spectrum of estimated signal through harmonic frequencies as in the estimated signal Ŝ3 which is seen at 11x fundamental frequency, 12x fundamental frequency, 15x fundamental frequency, and 16x fundamental frequency. 
Indoor and outdoor investigation comparison of photovoltaic thermal air collector Bahtiar Bahtiar; Muhammad Zohri; Ahmad Fudholi
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.037 KB) | DOI: 10.11591/eei.v9i4.2108

Abstract

Photovoltaic technology is one of renewable energy technology very hopeful, especially photovoltaic thermal system or PVT system. A PVT system solar air collector produces hot air and electricity simultaneously. In this study, indoor and outdoor investigation comparison of PVT system solar air collector has tested at the National University of Malaysia. The indoor and outdoor investigation conducted with variation mass flow rates from 0.01 kg/s to 0.05 kg/s at the solar intensity of 820 W/m2. Indoor and outdoor evaluation is conducted to precisely evaluate the performance improvement theorized by the researcher. The comparison between the indoor and outdoor outcome purposed to confirm each testing and attraction decision. The outdoor investigation outcomes were agreement with indoor results. Indoor investigation outcomes reliably with outdoor investigation outcomes indicated by accuracy results.
New feature selection based on kernel Zuherman Rustam; Sri Hartini
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (488.899 KB) | DOI: 10.11591/eei.v9i4.1959

Abstract

Feature selection is an essential issue in machine learning. It discards the unnecessary or redundant features in the dataset. This paper introduced the new feature selection based on kernel function using 16 the real-world datasets from UCI data repository, and k-means clustering was utilized as the classifier using radial basis function (RBF) and polynomial kernel function. After sorting the features using the new feature selection, 75 percent of it was examined and evaluated using 10-fold cross-validation, then the accuracy, F1-Score, and running time were compared. From the experiments, it was concluded that the performance of the new feature selection based on RBF kernel function varied according to the value of the kernel parameter, opposite with the polynomial kernel function. Moreover, the new feature selection based on RBF has a faster running time compared to the polynomial kernel function. Besides, the proposed method has higher accuracy and F1-Score until 40 percent difference in several datasets compared to the commonly used feature selection techniques such as Fisher score, Chi-Square test, and Laplacian score. Therefore, this method can be considered to use for feature selection
Cerebral infarction classification using multiple support vector machine with information gain feature selection Zuherman Rustam; Arfiani Arfiani; Jacub Pandelaki
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (581.68 KB) | DOI: 10.11591/eei.v9i4.1997

Abstract

Stroke ranks the third leading cause of death in the world after heart disease and cancer. It also occupies the first position as a disease that causes both mild and severe disability. The most common type of stroke is cerebral infarction, which increases every year in Indonesia. This disease does not only occur in the elderly, but in young and productive people which makes early detection very important. Although there are varied of medical methods used to classify cerebral infarction, this study uses a multiple support vector machine with information gain feature selection (MSVM-IG). MSVM-IG is a modification among IG Feature Selection and SVM, where SVM conducted doubly in the process of classification which utilizes the support vector as a new dataset. The data obtained from Cipto Mangunkusumo Hospital, Jakarta. Based on the results, the proposed method was able to achieve an accuracy value of 81%, therefore, this method can be considered to use for better classification result.
Capacitor bank controller using artificial neural network with closed-loop system Widjonarko Widjonarko; Cries Avian; Andi Setiawan; Moch. Rusli; Eka Iskandar
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (628.054 KB) | DOI: 10.11591/eei.v9i4.2411

Abstract

The problem of power factor in the industry is critical. This is due to the issue of low power factor that can make the vulnerability of industrial equipment damaged. This problem has been resolved in various ways, one of which is the Automatic Power Factor Correction, with the most popular device called capacitor bank. There are also many methods used, but several methods require certain calculations so the system can adapt to the new plant. In this study, researchers proposed a capacitor bank control system that can adapt to plants with different capacitor values without using any calculations by using an Artificial Neural Network with a closed-loop controller. The system is simulated using Simulink Matlab to know the performance with two testing scenarios. The first is changing the value of the power factor on the system and changing the value of the capacitor power at each bank, the second comparing it with the conventional methods. The results show that the system has been able to adapt to different capacitor power values and has a better performance than the conventional method in power factor oscillation due to the extreme power factor interference
HYBRID TSR-PSR PROTOCOL BASED FULL-DUPLEX ENERGY HARVESTING OVER RAYLEIGH FADING CHANNEL: SYSTEM PERFORMANCE ANALYSIS Tran Tin, Phu; Tran, Minh; Nguyen, Tan N.; Nguyen, Thanh-Long
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v9i4.2419

Abstract

Cooperative communication has been recently proposed in wireless communication systems for exploring the inherent spatial diversity in relay channels. In this work, we investigate the system performance of the energy harvesting full-duplex (FD) decode-and-forward (DF) hybrid TSR-PSR (TPSR) protocol relaying network. In the selection scheme, the best user selection protocol is proposed and investigated. Mainly we derive the closed-form expression for the outage probability, system throughput and the symbol error rate (SER) of the system. Numerical results are also presented by the Monte Carlo simulation to validate the theoretical analysis in connection with the all possible parameters in the comparison between TSPR, TSR and PSR cases. The research results show that TPSR case is better than the others in term of outage probability and SER.
Extended systematic clustering: Microdata protection by distributing semsitive values Widodo Widodo; Wahyu Catur Wibowo; Eko K. Budiardjo; Harry T. Y. Achsan
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.025 KB) | DOI: 10.11591/eei.v9i4.1963

Abstract

Anonymity data for multiple sensitive attributes in microdata publishing is a growing field at present. This field has several models for anonymizing such as k-anonymity and l-diversity. Generalization and suppression became a common technique in anonymize data. But, the real problem in multiple sensitive attributes is sensitive value distribution. If sensitive values do not distribute evenly to each quasi identifier group, it is potentially revealed to sensitive value holder. This research investigated on how the high-sensitive values are distributed evenly into each group. We proposed a novel method/algorithm for distributing high-sensitive values when it forms groups. This method distributes high-sensitive values evenly and varies high-sensitive values in a group. We called our method as extended systematic clustering since it is an extension of systematic clustering method. Diversity metrics was used for evaluating our method. Experiment result showed our method outperformed systematic clustering with average diversity value 0.9719 while systematic clustering 0.3316. 
Improved performance with fractional order control for asymmetrical cascaded H-bridge multilevel inverter Vemula Anil Kumar; Arounassalame Mouttou
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (507.981 KB) | DOI: 10.11591/eei.v9i4.1885

Abstract

This paper proposes a control scheme for seven level asymmetrical cascaded H-bridge multi level inverter (ACHBMLI) based on fractional order calculus. The seven level ACHBMLI consists of two H-bridges that are connected in series and are excited by different dc voltage sources. A simplified model is developed by assuming the small signal variation component is equal in both the H-bridges. A fractional order PID (FO-PID) controller is designed for the ACHBMLI using the simplified model. Simulation study shows the adequacy of FO-PID controller in giving an output voltage with minimum distortions. A conventional PID controller is also designed for ACHBMLI using the same simplified model. The performance of the ACHBMLI with FO-PID controller is compared with the performance of ACHBMLI with conventional PID controller. The simulation results prove the superiority of FO-PID controller in maintaining the output voltage of the ACHBMLI close to the reference voltage and in reducing the harmonic distortion of output voltage of the inverter. The simulation was done using MATLAB and the parameters of FO-PID controller was designed using FOMCON tool box.
Optimization of distribution network configuration with multi objective function based on improved cuckoo search algorithm Thuan Thanh Nguyen
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (591.535 KB) | DOI: 10.11591/eei.v9i4.1886

Abstract

This paper proposes an improved cuckoo search (ICSA) for solving the distribution network reconfiguration (NR) problem with multi-objective function. The membership functions are considered consisting of minimizing of power loss, load balancing among branches and among the feeders, node voltage deviation and switching operation numbers. ICSA is developed from the original CSA with adding the local search mechanism for exploiting around the current best solution. The effectiveness of the ICSA has validated on the 70-node and the 83-node practical systems. The obtained results have been compared to those from runner root algorithm (RRA) and other methods in the literature. The obtained results demonstrate that ICSA has high ability for searching the optimal solution with higher successful rate and better quality of obtained solution as well as smaller iterations compared to RRA and other methods. Therefore, ICSA is a reliable method for the multi-objective NR problems.

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