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Bulletin of Electrical Engineering and Informatics
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Core Subject : 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.
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Articles 52 Documents
Search results for , issue "Vol 9, No 4: August 2020" : 52 Documents clear
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.
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
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.
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
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.
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.
Mobile sensing in Aedes aegypti larva detection with biological feature extraction Dia Bitari Mei Yuana; Wahjoe Tjatur Sesulihatien; Achmad Basuki; Tri Harsono; Akhmad Alimudin; Etik Ainun Rohmah
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 (656.868 KB) | DOI: 10.11591/eei.v9i4.1993

Abstract

According to WHO, Dengue fever is the most critical and most rapidly mosquito-borne disease in the world over 50 years. Currently, the presence and detection of Aedes aegypti larvae (dengue-mosquitoes vector’s) are only quantified by human perception. In large-scale data, we need to automate the process of larvae detection and classification as much as possible. This paper introduces the new method to automate Aedes larvae. We use Culex larva for comparison. This method consists of data acquisition of recorded motion video, spatial movement patterns, and image statistical classification. The results show a significant difference between the biological movements of Aedes aegypti and Culex under the same environmental conditions. In 50 videos consisting of 25 Aedes larvae videos and 25 Culex larvae videos, the accuracy was 84%.
Design of constant output voltage DC-AC inverter for batteryless solar PV system Agus Risdiyanto; Bambang Susanto; Noviadi Arief Rachman; Anwar Muqorobin; Tinton Dwi Atmaja; Harjono P. Santosa
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 (459.791 KB) | DOI: 10.11591/eei.v9i4.2350

Abstract

This paper introduces a DC-AC inverter design that operates stand alone to deliver power from solar photovoltaic (PV) to the load directly without going through the battery. In batteryless solar PV, the output voltage of solar PV always varies according to solar irradiation, temperature, so that it becomes a challenge in modelling DC-AC inverter with constant output voltage. The design consists of a boost converter, h-bridge switching and driver, and LC filter to generate sinusoidal ac voltage as output to load. To ensure a constant inverter output voltage, the design equipped by a close loop PI controller based on voltage control mode. The design modelled and simulated by PSIM. PV dc input was set variation according to the irradiation value (W/m2) and the output connected to a load that has rated voltage of 220 Vac and 3.4 A of nominal current. The results show that in the irradiation variation 600-1500 W/m2, the inverter was able to maintain the output voltage of 220 Vac ± 0.91%, 50 Hz which is still in the voltage range based on standard. The efficiency produced by DC-AC inverter 97.7% at 600 W/m2 and 83.6% at 1500 W/m2.
Enhanced fractional frequency reuse approach for interference mitigation in femtocell networks Abdullah H. Alquhali; Mardeni Roslee; Mohamed Babikir Abdelgadir; Khaldon Kordi; Khalid S. Mohamed
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 (798.689 KB) | DOI: 10.11591/eei.v9i4.2355

Abstract

Small cell networks are expected to heavily be deployed in wireless communication networks due to it ability to enhance signals quality and spectrum utilisation. However, interference is posing a major threat to wireless communication especially cellular femtocell networks whereby its performance is degraded in dense deployment areas. For this reason, an enhanced fractional frequency reuse approach is proposed in this paper to mitigate the interference in femtocell networks. This is achieved by dividing the service area and frequency into three regions and three sets whereby each set is allocated different frequency set. The femtocell location is later obtained and assigned frequency in accordance to the region. The proposed approach helps in reducing the interference, boost the signal to interference plus noise (SINR), and enhance the throughput.