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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 12 Documents

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Search results for , issue "Vol 6, No 2: June 2017" : 12 Documents clear

Review of Detection DDOS Attack Detection Using Naive Bayes Classifier for Network Forensics Abdul Fadlil; Imam Riadi; Sukma Aji
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Distributed Denial of Service (DDoS) is a type of attack using the volume, intensity, and more costs mitigation to increase in this era. Attackers used many zombie computers to exhaust the resources available to a network, application or service so that authorize users cannot gain access or the network service is down, and it is a great loss for Internet users in computer networks affected by DDoS attacks. In the Network Forensic, a crime that occurs in the system network services can be sued in the court and the attackers will be punished in accordance with law. This research has the goal to develop a new approach to detect DDoS attacks based on network traffic activity were statistically analyzed using Naive Bayes method. Data were taken from the training and testing of network traffic in a core router in Master of Information Technology Research Laboratory University of Ahmad Dahlan Yogyakarta. The new approach in detecting DDoS attacks is expected to be a relation with Intrusion Detection System (IDS) to predict the existence of DDoS attacks.

Comparison of Tropical Thunderstorm Estimation between Multiple Linear Regression, Dvorak, and ANFIS Wayan Suparta; Wahyu Sasongko Putro
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Thunderstorms are dangerous and it has increased due to highly precipitation and cloud cover density in the Mesoscale Convective System area. Climate change is one of the causes to increasing the thunderstorm activity. The present studies aimed to estimate the thunderstorm activity at the Tawau area of Sabah, Malaysia based on the Multiple Linear Regression (MLR), Dvorak technique, and Adaptive Neuro-Fuzzy Inference System (ANFIS). A combination of up to six inputs of meteorological data such as Pressure (P), Temperature (T), Relative Humidity (H), Cloud (C), Precipitable Water Vapor (PWV), and Precipitation (Pr) on a daily basis in 2012 were examined in the training process to find the best configuration system. By using Jacobi algorithm, H and PWV were identified to be correlated well with thunderstorms. Based on the two inputs that have been identified, the Sugeno method was applied to develop a Fuzzy Inference System. The model demonstrated that the thunderstorm activities during intermonsoon are detected higher than the other seasons. This model is comparable to the thunderstorm data that was collected manually with percent error below 50%.

The Role of Organizational and Individual Factors in Knowledge Management System Acceptance Setiawan Assegaff
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

The aim of this study is to investigates the how individual and organizational factors influence people behavior in using knowledge management. This research applied Technology Acceptance Model (TAM) as a basis theory; TAM was enriched with individual and organizational factors for this study. A survey approach was conducted for data collection. Three of institutions in Banking Sector at Indonesia were invited to join this study and 215 knowledge workers were participated for the survey. Data from survey were analyzed through Structural Equations Model (SEM) using PLS (Partial Least Square) V2. The conclusion specify that ‘‘individual elements’’ and ‘‘organizational elements’’ are the significantly affect people behavior in KMS acceptance factors that influence knowledge worker behavior in knowledge sharing. However this study not found relationship between individual and organization factors and “perceived ease of use” construct with people behavior in accept KMS.

Stack Contention-alleviated Precharge Keeper for Pseudo Domino Logic Deepika Bansal; Brahmadeo Prasad Singh; Ajay Kumar
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v6i2.597

The dynamic circuits are supposed to offer superior speed and low power dissipation over static CMOS circuits. The domino logic circuits are used for high system performance but suffer from the precharge pulse degradation. This article provides different design topologies on the domino circuits to overcome the charge sharing and charge leakage with reference to the power dissipation and delay. The precharge keeper circuit has been proposed such that the keeper transistors also work as the precharge transistors to realize multiple output function. The performance improvement of the circuit’s analysis have been done for adders and logic gates using HSPICE tool. The proposed keeper techniques reveal lower power dissipation and lesser delay over the standard keeper circuit with less transistor count for different process variation.

Improving K-NN Internet Traffic Classification Using Clustering and Principle Component Analysis Adi Suryaputra Paramita
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

K-Nearest Neighbour (K-NN) is one of the popular classification algorithm, in this research K-NN use to classify internet traffic, the K-NN is appropriate for huge amounts of data and have more accurate classification, K-NN algorithm has a disadvantages in computation process because K-NN algorithm calculate the distance of all existing data in dataset. Clustering is one of the solution to conquer the K-NN weaknesses, clustering process should be done before the K-NN classification process, the clustering process does not need high computing time to conqest the data which have same characteristic, Fuzzy C-Mean is the clustering algorithm used in this research. The Fuzzy C-Mean algorithm no need to determine the first number of clusters to be formed, clusters that form on this algorithm will be formed naturally based datasets be entered. The Fuzzy C-Mean has weakness in clustering results obtained are frequently not same even though the input of dataset was same because the initial dataset that of the Fuzzy C-Mean is less optimal, to optimize the initial datasets needs feature selection algorithm. Feature selection is a method to produce an optimum initial dataset Fuzzy C-Means. Feature selection algorithm in this research is Principal Component Analysis (PCA). PCA can reduce non significant attribute or feature to create optimal dataset and can improve performance for clustering and classification algorithm. The resultsof this research is the combination method of classification, clustering and feature selection of internet traffic dataset was successfully modeled internet traffic classification method that higher accuracy and faster performance.

Entrepreneurship Through Start-ups in Hill Areas Using Photovoltaic Systems Chandani Sharma; Anamika Jain
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

There is large potential for generating solar power in Uttarakhand (India) endowed with natural resources. The extensive use of solar energy through solar PV panels in Distributed and Renewable Electricity Generation is significant to utilize multi climatic zones of hilly areas. In this regard, UREDA (Uttarakhand Renewable Energy Development Agency) targets to achieve a huge boost of solar PV battery backup with approved subsidy budget of INR 6 billion to 50 billion by 2019/20 under JNNSM (Jawaharlal Nehru National Solar Mission). This investment will increase productivity, enhance employment opportunities and improve quality of education. However, maximization of power output from panels used for same is achieved through use of MPPT (Maximum Power Point Trackers). The commercially installed solar power systems can be made to accomplish higher efficiency by implementing MPPT systems in start ups. In this paper, the effort is made to use MPPT system designed by intelligent controller for implementation in PV based utility systems. The regulated voltage output from MPPT system is obtained irrespective of fluctuations in environment. These variations are tested for changing temperature and irradiance due to shading or partial unavailability of sun. The results of same have been optimized through MATLAB/SIMULINK. The model designed is intended to be a beneficial source for PV engineers and researchers to provide high efficiency with the use of MPPT.

Optimized OFDM Model Using CMA Channel Equalization for BER Evaluation Pratima Manhas; M.K Soni
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Orthogonal Frequency Division Multiplexing (OFDM) is a type of Multicarrier Modulation (MCM) technique in which entire bandwidth is divided into large number of small sub-carriers and each subcarrier is transmitted parallel to achieve higher data rates. It has various applications like Digital Audio Broadcasting (DAB), Digital Video Broadcasting (DVB) and wireless LAN.OFDM technique is widely used in wireless communication system because of its very high data rate. The performance of FFT based OFDM system using Linear and cyclic channel coding and Constant Modulus Algorithm (CMA) equalizer is simulated using simulink model. The BER saving using the optimized proposed model with both linear and cyclic channel coding along with CMA equalizer is evaluated. The proposed work using cyclic channel coding with QPSK/QAM modulation and CMA as channel equalization under AWGN channel results in 52.6% and 96.3% BER reduction as compared to conventional OFDM model without channel coding, channel equalization and channel fading. So, CMA equalizer is used to enhance the performance of OFDM system.

Effectiveness of MPEG-7 Color Features in Clothing Retrieval Arsy Febrina Dewi; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Clothing is a human used to cover the body. Clothing consist of dress, pants, skirts, and others. Clothing usually consists of various colors or a combination of several colors. Colors become one of the important reference used by humans in determining or looking for clothing according to their wishes. Color is one of the features that fit the human vision. Content Based Image Retrieval (CBIR) is a technique in Image Retrieval that give index to an image based on the characteristics contained in image such as color, shape, and texture. CBIR can make it easier to find something because it helps the grouping process on image based on its characteristic. In this case CBIR is used for the searching process of Muslim fashion based on the color features. The color used in this research is the color descriptor MPEG-7 which is Scalable Color Descriptor (SCD) and Dominant Color Descriptor (DCD). The SCD color feature displays the overall color proportion of the image, while the DCD displays the most dominant color in the image. For each image of Muslim women's clothing, the extraction process utilize SCD and DCD. This study used 150 images of Muslim women's clothing as a dataset consistingclass of red, blue, yellow, green and brown. Each class consists of 30 images. The similarity between the image features is measured using the eucludian distance. This study used human perception in viewing the color of clothing.The effectiveness is calculated for the color features of SCD and DCD adjusted to the human subjective similarity. Based on the simulation of effectiveness DCD result system gives higher value than SCD.

Proactive Scheduling in Cloud Computing Ripandeep Kaur; Gurjot Kaur
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Autonomic fault aware scheduling is a feature quite important for cloud computing and it is related to adoption of workload variation. In this context, this paper proposes an fault aware pattern matching autonomic scheduling for cloud computing based on autonomic computing concepts. In order to validate the proposed solution, we performed two experiments one with traditional approach and other other with pattern recognition fault aware approach. The results show the effectiveness of the scheme.

A Hybrid Digital Watermarking Approach Using Wavelets and LSB Kumar, V. Ashok; Dharmaraj, C.; Rao, Ch. Srinivasa
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v6i2.650

The present paper proposes a novel approach called Wavelet based Least Significant Bit Watermarking (WLSBWM) for high authentication, security and copyright protection. The present approach utilizes Alphabet Pattern (AP) approach generating shuffled image in the first stage and Pellâ€™s Cat Map (PCM) is used for providing more security and strong protection from attacks. PCM applies on each 5Ã—5 sib images. A wavelet concept is used to reduce the dimensionality of the image until it equals to the size of the watermark image.Â Apply the Discrete Cosign Transform in the first stage later applies N levels Discrete Wavelet Transform (DWT) for reducing up to the size of the watermark image. Insert the water mark image in LHn Sub band of the wavelet image using LSB concept. Simulation results show that proposed technique produces better PSNR and similarity measure. The experimental results indicate that present approach is more reliable and secure efficient.The robustness of the proposed scheme is evaluated against various image-processing attacks.

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