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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 65 Documents
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Search results for , issue "Vol 16, No 3: December 2019" : 65 Documents clear
Twitter data analysis using hadoop ecosystems and apache zeppelin Stanly Wilson; Sivakumar R
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1490-1498

Abstract

The day-to-day life of the people doesn't depend only on what they think, but it is affected and influenced by what others think. The advertisements and campaigns of the favourite celebrities and mesmerizing personalities influence the way people think and see the world. People get the news and information at lightning speed than ever before. The growth of textual data on the internet is very fast. People express themselves in various ways on the web every minute. They make use of various platforms to share their views and opinions. A huge amount of data is being generated at every moment on this process. Being one of the most important and well-known social media of the present time, millions of tweets are posted on Twitter every day. These tweets are a source of very important information and it can be made use for business, small industries, creating government policies, and various studies can be performed by using it. This paper focuses on the location from where the tweets are posted and the language in which the tweets are written. These details can be effectively analysed by using Hadoop. Hadoop is a tool that is used to analyze distributed big data, streaming data, timestamp data and text data. With the help of Apache Flume, the tweets can be collected from Twitter and then sink in the HDFS (Hadoop Distributed File System). These raw data then analyzed using Apache Pig and the information available can be made use for social and commercial purposes. The result will be visualized using Apache Zeppelin.
A new methodology for technical losses estimation of radial distribution feeder Khairul Anwar Ibrahim; Mau Teng Au; Chin Kim Gan
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1126-1135

Abstract

Power distribution feeders is one of the key contributors of technical losses (TL) as it is typically large in numbers and scattered over large geographic areas. Traditional approach using classical formulation or time series load flow simulations to determine TL in each and every feeder and feeder sections in all distribution network require is an expensive exercise as it requires extensive modelling of the feeders and voluminous data. This paper presents a simple analytical approach to estimate monthly TL of a radial distribution feeder using analytical approach. TL for each feeder sections are evaluated on a monthly basis based on estimation of the load profile of the load points, peak power loss characteristics and loss factor. Total feeder TL are then estimated as the sum of all TL contributed by each feeder section. The developed models and procedure have been demonstrated through case studies performed on three (3) typical and representative feeders characterized by the different area served, number of feeder sections, load distribution and feeder length. The results shows close agreement (less than 5% differences) when compared with time series load flow simulations. With this model, the approach could be extended and applied to estimate TL of any radial distribution feeders of different configurations and characteristics
Comparison by simulation of PEGASIS and IEEPB routing protocols Samah Alnajdi; Fuad Bajaber
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1569-1576

Abstract

As the applications of wireless sensor networks (WSNs) became widely used throughout the years the importance of advanced sensor networks techniques increased as well. One of the main techniques used in WSNs is hierarchical routing which mainly aims to reduce the consumption of sensor nodes energy by assigning different roles to the sensor nodes to create multi-layer scheme for data transmission. This paper embraces a simulation for two known hierarchical routing protocols: Power-Efficient Gathering in Sensor Information Systems (PEGASIS) protocol and an Improved Energy-Efficient PEGASIS-Based (IEEPB) protocol. Both protocols aim to reduce the transmission distance in order to save the nodes energy by performing chain-based clustering. For evaluation, we measured the residual energy and control overhead throughout the network operation time and the results showed major flaws in both protocols such as long link problem and poor leader selection method in PEGASIS. Moreover, high nodes density problem in IEEPB.
Investigation of indoor propagation of WLAN signals Mohammed Sameer Salim; khalil Hassan Sayidmarie; Abdullah Hassan Aboud
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1356-1363

Abstract

The propagation of radio waves inside a typical university building is investigated by simulation and measurements. The Line of sight (LOS) and Obstructed Line of sight (OLOS) propagation scenarios were considered. The received power from a WLAN access point operating at 2.45GHz was determined from the simulations and measurements at various positions, orientations, and heights of the Tx and Rx antennas. The path loss exponents were estimated from the obtained simulation and measurement results of the received power variation with distance. The obtained path loss exponent values were found between 1.15-1.63 for LOS propagation and 2.14-2.55 for OLOS.
Developed artificial neural network based human face recognition Maryam Mahmood Hussein; Ammar Hussein Mutlag; Hussain Shareef
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1279-1285

Abstract

Face recognition has become one of the most important challenging problems in personal computer-human interaction, video observation, and biometric. Many algorithms have been developed in the recent years. Theses algorithms are not sufficiently robust to address the complex images. Therefore, this paper proposes soft computing algorithm based face recognition. One of the most promising soft computing algorithms which is back-propagation artificial neural network (BP-ANN) has been proposed. The proposed BP-ANN has been developed to improve the performance of the face recognition. The implementation of the developed BP-ANN has been achieved using MATLAB environment. The developed BP-ANN requires supervised training to learn how to anticipate results from the desired data. The BP-ANN has been developed to recognition 10 persons. Ten images have been used for each person. Therefore, 100 images have been utilized to train the developed BP-ANN. In this research 50 images have been used for testing purpose. The results show that the developed BP-ANN has produced a success ratio of 82%.
Annealing strategy for an enhance rule pruning technique in ACO-Based rule classification Hayder Naser Khraibet AL-Behadili; Ku Ruhana Ku-Mahamud; Rafid Sagban
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1499-1507

Abstract

Ant colony optimization (ACO) was successfully applied to data mining classification task through ant-mining algorithms. Exploration and exploitation are search strategies that guide the learning process of a classification model and generate a list of rules. Exploitation refers to the process of intensifying the search for neighbors in good regions, whereas exploration aims towards new promising regions during a search process. The existing balance between exploration and exploitation in the rule construction procedure is limited to the roulette wheel selection mechanism, which complicates rule generation. Thus, low-coverage complex rules with irrelevant terms will be generated. This work proposes an enhancement rule pruning procedure for the ACO algorithm that can be used in rule-based classification. This procedure, called the annealing strategy, is an improvement of ant-mining algorithms in the rule construction procedure. Presented as a pre-pruning technique, the annealing strategy deals first with irrelevant terms before creating a complete rule through an annealing schedule. The proposed improvement was tested through benchmarking experiments, and results were compared with those of four of the most related ant-mining algorithms, namely, Ant-Miner, CAnt-Miner, TACO-Miner, and Ant-Miner with hybrid pruner. Results display that our proposed technique achieves better performance in terms of classification accuracy, model size, and computational time. The proposed annealing schedule can be used in other ACO variants for different applications to improve classification accuracy.
Network intrusion detection system by using genetic algorithm Hamizan Suhaimi; Saiful Izwan Suliman; Ismail Musirin; Afdallyna Fathiyah Harun; Roslina Mohamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1593-1599

Abstract

Developing a better intrusion detection systems (IDS) has attracted many researchers in the area of computer network for the past decades. In this paper, Genetic Algorithm (GA) is proposed as a tool that capable to identify harmful type of connections in a computer network. Different features of connection data such as duration and types of connection in network were analyzed to generate a set of classification rule. For this project, standard benchmark dataset known as KDD Cup 99 was investigated and utilized to study the effectiveness of the proposed method on this problem domain. The rules comprise of eight variables that were simulated during the training process to detect any malicious connection that can lead to a network intrusion. With good performance in detecting bad connections, this method can be applied in intrusion detection system to identify attack thus improving the security features of a computer network.
The sensorless control system for controlling the speed of direct current motor Khac-Khiem Nguyen; Trong-Thang Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1171-1178

Abstract

This research aims to propose an algorithm for controlling the speed of the Direct Current (DC) motor in the absence of the sensor of speed. Based on the initial mathematical model of DC motor, the authors build the dynamic state equation of DC motor, and then build an estimation model to determine the speed of the DC motor without a sensor. The advantages of the proposed method are demonstrated through the closed-loop control model using the PID controller. In order for the results to be objective, we assume that the parameters of the DC motor in the estimation model are not known correctly. The results show that the quality of control in the absence of a sensor is equivalent to the case with the sensor.
LQR control of interleaved double dual boost converter for electrical vehicles and renewable energy conversion J. S. V. Siva Kumar; P. Mallikarjunarao
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1240-1248

Abstract

The automobile industry is one of the major industries that are having its new innovations at a great pace according to the requirements of the day-to-day life. Due to the usage of conventional vehicles on a large scale which usually use petroleum products as fuel, is leading to a vast environmental effect, mainly due to the emission of greenhouse gases. So in order to reduce the ill effects of the greenhouse gas emissions great efforts are being put in   manufacturing of electrical vehicles. Among the currently available greenhouse technologies the fuel cell provides high energy density in spite of its expenses. So, in this aspect a required mechanism has to be adopted to make it energy efficient and affordable. In order to overcome the drawback of fuel cell i.e. low output voltage, the boost converters are to be used and to be more precise Non-isolated Interleaved Double Dual Boost (IDDB) converters are recommended which makes it efficient and also the reduction of overall vehicle weight can be achieved. The LQR control technique is applied in this work to make the transient response of the fuel cell powered IDDB converter for various load conditions effective. The verification of results is done with simulation techniques using MATLAB/Simulink.
Solutions of reaction-diffusion equations using similarity reduction and HSSOR iteration Nur Afza Mat Ali; Rostang Rahman; Jumat Sulaiman; Khadizah Ghazali
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1430-1438

Abstract

Similarity method is used in finding the solutions of partial differential equation (PDE) in reduction to the corresponding ordinary differential equation (ODE) which are not easily integrable in terms of elementary or tabulated functions. Then, the Half-Sweep Successive Over-Relaxation (HSSOR) iterative method is applied in solving the sparse linear system which is generated from the discretization process of the corresponding second order ODEs with Dirichlet boundary conditions. Basically, this ODEs has been constructed from one-dimensional reaction-diffusion equations by using wave variable transformation. Having a large-scale and sparse linear system, we conduct the performances analysis of three iterative methods such as Full-sweep Gauss-Seidel (FSGS), Full-sweep Successive Over-Relaxation (FSSOR) and HSSOR iterative methods to examine the effectiveness of their computational cost. Therefore, four examples of these problems were tested to observe the performance of the proposed iterative methods.  Throughout implementation of numerical experiments, three parameters have been considered which are number of iterations, execution time and maximum absolute error. According to the numerical results, the HSSOR method is the most efficient iterative method in solving the proposed problem with the least number of iterations and execution time followed by FSSOR and FSGS iterative methods.

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