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Bulletin of Electrical Engineering and Informatics

EEI
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Published by Universitas Ahmad Dahlan

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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.

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Articles 2,901 Documents

70 71 72 73 74

Controller selection in software defined networks using best-worst multi-criteria decision-making Esmaeil Amiri; Emad Alizadeh; Mohammad Hossein Rezvani
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Controllers are the key component of Software-defined Network (SDN) architecture. Given the diversity of open SDN controllers, the following question arises for the network administrators: How can we choose the appropriate SDN controller? Different characteristics of the controllers have greatly increased the complexity of the right decision. Multi-Criteria Decision-making Methods (MCDMs) is a family of robust mathematical tools to address complex problems regarding multiple objectives. In this paper, we study the most important features of SDN controllers. To this end, we compare the well-known SDN controllers including NOX, POX, Beacon, Floodlight, Ryu, ODL, and ONOS. Leveraging a novel MCDM technique called the Best–Worst Multi-criteria (BWM), we find the most appropriate SDN controller. We solve an optimization problem and evaluate its performance in terms of significant criteria such as throughput and latency. Initial evaluation revealed that the ONOS and ODL have the highest throughput, while the lowest throughputs belong to the NOX, POX, and Ryu. However, final evaluation concerning all criteria confirmed the robustness of the ONOS and the ODL compared to other controllers.

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

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.

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

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.

Spell corrector for Bangla language using Norvig’s algorithm and Jaro-Winkler distance Istiak Ahamed; Maliha Jahan; Zarin Tasnim; Tajbia Karim; S. M. Salim Reza; Dilshad Ara Hossain
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.v10i4.2410

In the online world, especially in the social media platform most of us write without much regard to correct spelling and grammar. The spelling mistakes are much larger in proportion when it comes to Bangla language. In our paper, we presented a method for error detection and correction in Bangla words' spellings. Our system could detect a misspelled Bangla word and provide two following services-suggesting correct spellings for the word and correcting the word. We had used Norvig's algorithm for the purpose but instead of using probabilities of the words to prepare the suggestions and corrections, we had used Jaro-Winkler distance. The previous works done in this field for Bangla language are either very slow or offers less accuracy. Our system successfully achieved a 97% accuracy when evaluated with 1000 Bangla words.

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

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%.

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

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

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

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

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

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.

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