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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 52 Documents
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Search results for , issue "Vol 11, No 3: September 2018" : 52 Documents clear
Quadratic Support Vector Machine For The Bomba Traditional Textile Motif Classification Nuraedah Nuraedah; Muhammad Bakri; Anita Ahmad Kasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1004-1014

Abstract

The Bomba textile is one of the textile fabrics in Indonesia used in a province called Sulawesi Tengah. Bomba Textile has a unique pattern and has a philosophical meaning in human life in Sulawesi Tengah. Bomba Textile has many motif patterns and varied colors. The problem in this research is the difficulty in classifying every The Bomba textile motif in each class. Data classification is needed to recognize the motif of each Bomba textile pattern and to cluster it into the appropriate class. The features used to classify the Bomba textile motif is the textural feature. Texture features obtained from Gray-Level Co-occurrence matrices (GLCM) method consisting of energy, contrast, homogeneity and correlation with four angles 0°, 45°, 90°, and 135°. This research will implement Quadratic Vector Machine (QSVM) method with texture feature on Bomba textile pattern. The use of a single texture feature with angles 90° has an accuracy of 90.3%. The incorporation of texture features by involving all features at all angles can improve the accuracy of the classification model. This research produces a model of motif classification on the Bomba textile which has the classification accuracy of 94.6% and error rate of 5.4%.
Design of “ 32 ” Point Split Radix b ased Multipath Delay Commutator FFT Architecture for Low Power Applications A. Manimaran; ABY K. Thomas
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1042-1047

Abstract

FFT is used in Modern high speed signal processing application. In aforementioned technologies that tends to operate in various operational modes. To implement FFT obviously it not only needs to meet high throughput demand and also it needed to scalable cater selectable N point FFT. Our contribution to this paper is two-fold of our existing method, as proposes for the split radix using Multipath Delay Commutator (MDC) algorithm has the least complex design and less multiplications comparing to radix-2 algorithm. So that it can able to reduce power consumption and area than our existing work. The implementation of power efficient hardware of split radix FFT (SRFFT) is built up by pruning excessive computation. Leveraging this potential, a new architecture of a configurable SRFFT processor is first developed so that unnecessary computations, which yield zeros at the output, are pruned. Simulations show that maximum power saving of around 20% is achieved. The proposed algorithm consists of mixed radix butterflies, whose structure is more regular. It has the conjugate-pair version, which requires less memory.
Modified AES for Text and Image Encryption Heidilyn V. Gamido; Ariel M. Sison; Ruji P. Medina
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp942-948

Abstract

Advanced Encryption Standard (AES) is one of the most frequently used encryption algorithms. In the study, the Advanced Encryption Standard is modified to address its high computational requirement due to the complex mathematical operations in MixColumns Transformation making the encryption process slow. The modified AES used Bit Permutation to replace the MixColumns Transformation in AES since bit permutation is easy to implement and it does not have any complex mathematical computation. Results of the study show that the modified AES algorithm exhibited increased efficiency due to the faster encryption time and reduced CPU usage. The modified AES algorithm also yielded higher avalanche effect which improved the performance of the algorithm.
Identification of Rainfall Patterns on Hydrological Simulation Using Robust Principal Component Analysis S.M. Shaharudin; N. Ahmad; N.H. Zainuddin; N.S. Mohamed
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1162-1167

Abstract

A robust dimension reduction method in Principal Component Analysis (PCA) was used to rectify the issue of unbalanced clusters in rainfall patterns due to the skewed nature of rainfall data. A robust measure in PCA using Tukey’s biweight correlation to downweigh observations was introduced and the optimum breakdown point to extract the number of components in PCA using this approach is proposed. A set of simulated data matrix that mimicked the real data set was used to determine an appropriate breakdown point for robust PCA and  compare the performance of the both approaches. The simulated data indicated a breakdown point of 70% cumulative percentage of variance gave a good balance in extracting the number of components .The results showed a  more significant and substantial improvement with the robust PCA than the PCA based Pearson correlation in terms of the average number of clusters obtained and its cluster quality.
GWO Based Optimal Reactive Power Coordination of DFIG, ULTC and Capacitors Mogaligunta Sankaraiah; Sanna Suresh Reddy; M Vijaya Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp805-813

Abstract

Wind is available with free of cost anywhere in the world, this wind can be used for power generation due to many advantages. This attracts the researchers to work on wind power plants. The presence of wind power plants on distribution system causes major influence on voltage controlled devices (VCDs) in terms of life of the devices. Therefore, this paper proposes grey wolf optimization method (GWO) together with forecasted load one day in advance. VCDs are on load tap changer (ULTC) and capacitors (CS), there are two main objectives first one is curtail of distribution network (DN) loss and second one is curtailing of ULTC and CS switching’s. Objectives are achieved by controlling the reactive power of DFIG in coordination with VCDs. The proposed method is planned and applied in Matlab/Simulink on 10KV practical system with DFIG located at different locations. To validate the efficacy of GWO, results are compared with conventional and dynamic programming methods without profane grid circumstances.
A Radio Signal Strength Based Localization Error Optimization Technique for Wireless Sensor Network Sudha H. Thimmaiah; Mahadevan G
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp839-847

Abstract

Wireless Sensor Networks (WSN) is useful in collecting data from various sensor devices that are distributed over a network which is generally positioned in a stationary manner. Wireless sensor based communication system is an ever growing sector in the industry of communication. Wireless infrastructure is a network that enables correspondence between various devices associated through an infrastructure protocol. Finding the position or location of sensor node (Localization) is an important factor in sensor network for proving efficient service to end user. The existing technique proposed so for adopt AOA (Angle of Arrival), TOA (Time of Arrival) etc… suffers in estimating the likelihood of localization error and induces high cost of deployment. To cater this in this work the author proposes a cost effective RSS (Received signal strength) based localization technique and also proposes an adaptive information estimation to reduce or approximate the localization error in wireless sensor network. The author compares our proposed localization model with existing protocol and analyse its efficiency.
A Review of Crude Oil Prices Forecasting using Hybrid Method Nurull Qurraisya Nadiyya Md-Khair; Ruhaidah Samsudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1114-1120

Abstract

Crude oil is considered as a crucial energy source in modern days. Consequently, the fluctuation of crude oil prices can cause a significant impact on economic activities. Researchers have proposed many hybrid forecasting models on top of single forecasting methods which are utilized to predict crude oil prices movement more accurately. Nevertheless, many limitations still existed in hybrid forecasting models and models that can predict crude oil prices as accurate as possible is required. The motivations of this review paper are to identify and assess the mostly used crude oil prices forecasting methods and to analyse their current limitations. 12 studies that used “decomposition-and-ensemble” framework was selected for review. Wavelet transform is identified as the mostly used data decomposition method while some limitations have been recognized. Future researches should include more studies to further elucidate the limitations in existing forecasting method so that subsequent forecasting methods can be improved.
Design and Analysis of a Smart Blind Stick for Visual Impairment Zulkhairi Mohd Yusof; Md Masum Billah; Kushsairy Kadir; Muhamad Amirul Sunni Bin Rohim Rohim; Haidawati Nasir; M. Izani; A. Razak
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp848-856

Abstract

For a long time, visually impaired person uses a white cane to guide their way when travel outside. The white cane has been useful for the blinds in improving their mobility but unfortunately the white cane has its limitation. One of the shortcomings of the white cane is that, it could only detect the obstacles that are within the contact ranges of the white cane. This problem sometimes could cause the blind person to be in trouble because of insufficient time to detect and warn new obstacles in front of the blind person. This research proposes a walking stick system that has two functions; to classify an obstacles height whether it is low or high and to detect a front hole. The ability to detect the height of an obstacle will help the visually impaired to either step over or avoid the obstacle. The ability to detect a hole should help the visually impaired to avoid it in time. The walking stick will use two ultrasonic sensors for the detection of obstacle height, and a laser sensor for the detection of hole. A controller will be used to monitor and analyze the data from the sensors and feedback to the user through a vibration sensor and buzzer. The algorithm to differentiate the height of obstacles is working well and it is able to differentiate high or low obstacles. The laser ranging sensor has successfully been tested for hole detection. Therefore, the walking stick with ultrasonic and laser sensors will help more visually impaired to move around much faster and feeling more safer due to improved warning system for their movement.
A Review of Electromyography Signal Analysis Techniques for Musculoskeletal Disorders T. N. S. Tengku Zawawi; A. R. Abdullah; M.H. Jopri; Tole Sutikno; N.M. Saad; R. Sudirman
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1136-1146

Abstract

Social Security Organisation (SOCSO) Malaysia has reported that the incidence of work related to musculoskeletal disorders (MSDs) has been growing planetary in the manufacturing industry. MSDs are the result of repetitive, forceful or awkward movements on our body and or body parts of bones, joints, ligaments and other soft tissues. Workplace pains and strains can be serious and disabling for workers, causing pain and suffering ranging from discomfort to severe disability. To overcome this problem, Electromyography is proper to use in Health Screening Program (HSP) it to monitor darn diagnose the muscle’s performance for their patient and know the exact localization of muscle pain. The previous researchers has been explore of several in EMG analysis techniques and features proposed in time, frequency and time-frequency domain analysis. This review of common EMG signal processing techniques is proposed by assembling from simple to complex analysis techniques to give the overview information for the other researcher. This is because; the suitable selection of a method and its features settings will ensure readability of the time-frequency representations and reliability of results. The strongest correspond with time-frequency characteristic and resolution also reducing cross term for bilinear will consider it as the optimal method.
Cascaded Neural Network Based Data Mining Strategy for Cloud Intrusion Detection P Purniemaa; R Jagadeesh Kannan
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i3.pp1094-1101

Abstract

In recent years data mining has acquired huge popularity in the field of knowledge discovery. Thus, this approach has inspired several researches for anomaly detection, fraud detection and intrusion detection with higher accuracy, all round generalization of the problem and its sub cases; all giving higher performance in conditions subjected to continuous alteration. Though there remain quite a few challenging problems in design and implementation of a data mining based cloud intrusion detection system, as deception tactics and modeling of behavior remains a daunting problem to compute for anomaly owing to massive size of data to process in reasonable time. In this study we present a cascaded neural network based data mining strategy for cloud intrusion detection systems (IDSs) and presents the comparison and performance results tested on DARPA Intrusion Detection (ID) Data Sets, Knowledge Discovery and Data Mining Cup, NSL-KDD dataset. The study exhibits numerous advantages offered by the presented method and give reliable results of anomaly detection in real time scenario.

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