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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 66 Documents
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Search results for , issue "Vol 24, No 2: November 2021" : 66 Documents clear
A simple, effective distance and density based outlier detection algorithm Sajidha S. A.; Udai Agarwal; Pruthviraj R. P.; Sparsh Agarwal; Nisha V. M.; Amit Kumar Tyagi
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1141-1148

Abstract

Outliers are eccentric data points with anomalous nature. Clustering with outliers has received a lot of attention in the data processing community. But, they inordinately affect the quality of the results obtained in case of popular clustering algorithms during the process of finding an optimal solution. In this work, we propose a novel method to classify the data points with grouping characteristics as either an outlier or not. We use both distance and density of a particular data point with respect to the rest of the data points for this process. Distances are used to find the points at the extremities while the densities are used to identify the data points at the sparsest spaces. Further, every data model has to take into account the aspect of generalization in order to work robustly even in out of the box situations. Hence, our approach provides a generalization aspect to the model. The accuracy of the proposed work is measured using area under curve (AUC) was found the highest for cardioto data set -AUC value-0.90 and second highest AUC value was obtained for Spambase data set -0.52 and several other datasets are used to demonstrate the usage of the model proposed.
Intrusion detection system based on bagging with support vector machine Ali Khalid Hilool; Soukaena H. Hashem; Shatha H. Jafer
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1100-1106

Abstract

Due to their rapid spread, computer worms perform harmful tasks in networks, posing a security risk; however, existing worm detection algorithms continue to struggle to achieve good performance and the reasons for that are: First, a large amount of irrelevant data affects classification accuracy. Second, individual classifiers do not detect all types of worms effectively. Third, many systems are based on outdated data, making them unsuitable for new worm species. The goal of the study is to use data mining algorithms to detect worms in the network because they have a high ability to detect new types accurately. The proposal is based on the UNSW NB15 dataset and uses a support vector machine to train and test the ensemble bagging algorithm. To detect various types of worms efficiently, the contribution suggests combining correlation and Chi2 feature selection method called Chi2-Corr to select relevant features and using support vector machine (SVM) in the bagging algorithm. The system achieved accuracy reaching 0.998 with Chi2-Corr, and 0.989, 0.992 with correlation and chi-square separately.
IMUW-APP: An instrument for measuring the usability of web applications Ayad Hameed Mousa; Mowafak K. Mohsen; Ali M. Alnasrawi; Intedhar Shakir Nasir
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1183-1194

Abstract

Conventional usability measurement methods for measuring web applications are costly, sometimes time-consuming, and may require professionals. The frameworks, methods, approaches, and tools in which web applications are designed can fully support these limitations. The main issue is to speed up the evaluation process of websites in an effortless manner. To overcome this limitation, this paper proposes an instrument that can use for measuring the usability of web applications (IMUW-APP). A systematic literature review was utilized to determine the instrument dimensions and their items. The validity and reliability test were conducted via face and content validity, goodness testing, and pilot study. Cronbach's Alpha, factor loading, Kaiser-Meyer-Olkin, and Barlett's test were +calculated to ensure the validity and reliability of the proposed instrument. In the light of our analyses, the obtained findings indicate that the proposed instrument (IMUWAPP) is workable and can adapt. Besides, a case study is used to verify the proposed instrument to evaluate a university website. The collecting data have been analyzed and visualized. Ultimately, the overall findings have highlighted.
Electricity consumption forecasting using DFT decomposition based hybrid ARIMA-DLSTM model Osman Yakubu; Narendra Babu C.
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1107-1120

Abstract

Forecasting electricity consumption is vital, it guides policy makers and electricity distribution companies in formulating policies to manage production and curb pilfering. Accurately forecasting electricity consumption is a challenging task. Relying on a single model to forecast electricity consumption data which comprises both linear and nonlinear components produces inaccurate results. In this paper, a hybrid model using autoregressive integrated moving average (ARIMA) and deep long short-term memory (DLSTM) model based on discrete fourier transform (DFT) decomposition is presented. Aided by its superior decomposition capability, filtering using DFT can efficiently decompose the data into linear and nonlinear components. ARIMA is employed to model the linear component, while DLSTM is applied on the nonlinear component; the two predictions are then combined to obtain the final predicted consumption. The proposed techniques are applied on the household electricity consumption data of France to obtain forecasts for one day, one week and ten days ahead consumption. The results reveal that the proposed model outperforms other benchmark models considered in this investigation as it attained lower error values. The proposed model could accurately decompose time series data without exhibiting a performance degradation, thereby enhancing prediction accuracy.
New algorithm for clustering unlabeled big data Marwan B. Mohammed; Wafaa AL-Hameed
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1054-1062

Abstract

The clustering analysis techniques play an important role in the area of data mining. Although from existence several clustering techniques. However, it still to their tries to improve the clustering process efficiently or propose new techniques seeks to allocate objects into clusters so that two objects in the same cluster are more similar than two objects in different clusters and careful not to duplicate the same objects in different groups with the ability to cover all data as much as possible. This paper presents two directions. The first is to propose a new algorithm that coined a name (MB Algorithm) to collect unlabeled data and put them into appropriate groups. The second is the creation of a lexical sequence sentence (LCS) based on similar semantic sentences which are different from the traditional lexical word chain (LCW) based on words. The results showed that the performance of the MB algorithm has generally outperformed the two algorithms the hierarchical clustering algorithm and the K-mean algorithm.
Experimental study of through the wall imaging for the detection of vital life signs using SFWR Pardhu Thottempudi; Vijay Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp825-830

Abstract

Now a day’s defence applications associated to novel, army and military war fields are required wall imaging discrimination. As of now many wallimaging techniques are designed but didn’t identify the vital signs behind walls with accurate working. Therefore, a novel advance wall image tracking method is required identification of human target. An experimental study on through the wallimaging (TWI) to detect the life signs using sweep frequency continuous wave radar (SFCWR) is explained in this paper. The proposed system consists of agilent vector network analyzer (VNA) (Agilent E5071B ENA), horn antenna and a computer. The information of heart beat and the breathing can be a shift identification routine was used to collect information from the back scattering electric current. The outcomes of the procedure give the information of heart beat and breathing signs of real human being.
Compact MIMO antenna using dual-band for fifth-generation mobile communication system Debani Prasad Mishra; Kshirod Kumar Rout; Surender Reddy Salkuti
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp921-929

Abstract

This paper presents the design of a multiple-input and multiple-output (MIMO) antenna for a fifth-generation (5G) smartphone that will work in dual-band. The antenna proposed in this work operates at 2 frequency ranges, i.e., (3300-3600) MHz and (4800-5000) MHz. The antenna design consists of four antennas that are placed perpendicular to the edge of the system and this makes it different from the traditional 5G antennas. The area of each antenna on the side frames is (3.9×17 mm), and hence can be used in ultra-thin smartphones for 5G applications. The reflection coefficient obtained in the simulations is less than -6 dB for the required band, which suggests that the required impedance matching is obtained. The antenna proposed is designed by using central time zone (CST) microwave studio.
A series-connected switched source and an H-bridge based multilevel inverter Siva Pachipala; Amarsrinadh Guda; Mentimi Sandeep Babu; Veeranarayana B.; K. V. S. Ramachandra Murthy; Abhilash Tirupathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp673-679

Abstract

An inverter circuit is promoted in this paper, using series-connected switched dc sources along with an H-bridge circuit with optimized circuit elements like switching devices and diode clamped (DC) sources. This configuration uses DC supplies that can be strung together in series to create a significant voltage level. This topology consists of two parts, namely: 1) level production part and 2) polarity production part. The combination of some of the dc sources and switching devices completes the level production part. The H-bridge in the presented structure produces the polarity generation part. The DC-link capacitors are not needed in this design. There is a full presentation of the operating modes and modeling process of the proposed converter. Finally, in the MATLAB/SIMULINK setting the proposed topology is simulated and output current and voltage results have been examined.
Impact assessment of simultaneous operation of photovoltaic and cogeneration power plants on industrial distribution system B. Koti Reddy; Amit Kumar Singh
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp649-660

Abstract

Industries with co-generation plants face unprecedented problems due to penetration of renewable energy systems such as solar power on their existing distribution networks. These problems are caused by intermittent solar power. To this end, this paper provides a detailed investigation of the effects due to sudden changes in solar power on an existing industrial distribution network connected to co-generation plants. Moreover, the case studies in this work consider simultaneous operation of a large industry having co-generation captive power plant and large scale solar photovoltaic power plant. The real-time field data for the past three years are used to check the performance of solar photovoltaic power plant, load management, power quality and other concerning issues on the distribution network. In addition to the real-time data, the simulations were performed for the solar power output under different solar irradiance conditions. Moreover, these simulations are used to assess photovoltaic integration effects on a distribution system having a co-generation captive power plant. Finally, this paper put forward photovoltaic integration guidelines to industries and policymakers interested to carry out the integration studies in the future.
Modified limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm for unconstrained optimization problem Muna M. M. Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 2: November 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i2.pp1027-1035

Abstract

The use of the self-scaling Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is very efficient for the resolution of large-scale optimization problems, in this paper, we present a new algorithm and modified the self-scaling BFGS algorithm. Also, based on noticeable non-monotone line search properties, we discovered and employed a new non-monotone idea. Thereafter first, an updated formula is exhorted to the convergent Hessian matrix and we have achieved the secant condition, second, we established the global convergence properties of the algorithm under some mild conditions and the objective function is not convexity hypothesis. A promising behavior is achieved and the numerical results are also reported of the new algorithm.

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