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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 57 Documents
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Search results for , issue "Vol 12, No 2: November 2018" : 57 Documents clear
Ideal Huffman Code for Lossless Image Compression for Ubiquitous Access T Kavitha; K. Jayasankar
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp765-774

Abstract

Compression technique is adopted to solve various big data problems such as storage and transmission. The growth of cloud computing and smart phone industries has led to generation of huge volume of digital data. Digital data can be in various forms as audio, video, images and documents. These digital data are generally compressed and stored in cloud storage environment. Efficient storing and retrieval mechanism of digital data by adopting good compression technique will result in reducing cost. The compression technique is composed of lossy and lossless compression technique. Here we consider Lossless image compression technique, minimizing the number of bits for encoding will aid in improving the coding efficiency and high compression. Fixed length coding cannot assure in minimizing bit length. In order to minimize the bits variable Length codes with prefix-free codes nature are preferred. However the existing compression model presented induce high computing overhead, to address this issue, this work presents an ideal and efficient modified Huffman technique that improves compression factor up to 33.44% for Bi-level images and 32.578% for Half-tone Images. The average computation time both encoding and decoding shows an improvement of 20.73% for Bi-level images and 28.71% for Half-tone images. The proposed work has achieved overall 2% increase in coding efficiency, reduced memory usage of 0.435% for Bi-level images and 0.19% for Half-tone Images. The overall result achieved shows that the proposed model can be adopted to support ubiquitous access to digital data.
Jatropha Curcas Disease Identification With Extreme Learning Machine Triando Hamonangan Saragih; Diny Melsye Nurul Fajri; Wayan Firdaus Mahmudy; Abdul Latief Abadi; Yusuf Priyo Anggodo
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp883-888

Abstract

Jatropha is a plant that has many functions, but this plant can be attacked by various diseases. Expert systems can be applied in identifying so that can help both farmers and extension workers to identify the disease. one of method that can be used is Extreme Learning Machine. Extreme Learning Machine is a method of learning in Neural Network which has a one-time iteration concept in each process. In this study get a maximum accuracy of 66.67% with an average accuracy of 60.61%. This proves the identification using Extreme Learning Machine is better than the comparison method that has been done before.
Celebrity Face Recognition using Deep Learning Nur Ateqah Binti Mat Kasim; Nur Hidayah Binti Abd Rahman; Zaidah Ibrahim; Nur Nabilah Abu Mangshor
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp476-481

Abstract

Face recognition is one of the well studied problems by researchers in computer visions.  Among the challenges of this task are the occurrence of different facial expressions like happy or sad, and different views of the images such as front and side views.  This paper experiments a publicly available dataset that consists of 200,000 images of celebrity faces. Deep Learning technique is gaining its popularity in computer vision and this paper applies this technique for face recognition problem.  One of the techniques under deep learning is Convolutional Neural Network (CNN).  There is also pre-trained CNN models that are AlexNet and GoogLeNet, which produce excellent accuracy results.  The experimental results indicate that AlexNet is better than basic CNN and GoogLeNet for face recognition.
YouTube Spam Comment Detection Using Support Vector Machine and K–Nearest Neighbor Aqliima Aziz; Cik Feresa Mohd Foozy; Palaniappan Shamala; Zurinah Suradi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp612-619

Abstract

Social networking such as YouTube, Facebook and others are very popular nowadays. The best thing about YouTube is user can subscribe also giving opinion on the comment section. However, this attract the spammer by spamming the comments on that videos. Thus, this study develop a YouTube detection framework by using Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN). There are five (5) phases involved in this research such as Data Collection, Pre-processing, Feature Selection, Classification and Detection. The experiments is done by using Weka and RapidMiner. The accuracy result of SVM and KNN by using both machine learning tools show good accuracy result. Others solution to avoid spam attack is trying not to click the link on comments to avoid any problems.
Performance Evaluation of SW Algorithm on NVIDIA GeForce GTX TITAN X Graphic Processing Unit (GPU) Ahmad Hasif Azman; Syed Abdul Mutalib Al Junid; Abdul Hadi Abdul Razak; Mohd Faizul Md Idros; Abdul Karimi Halim; Fairul Nazmie Osman
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp670-676

Abstract

Nowadays, the requirement for high performance and sensitive alignment tools have increased after the advantage of the Deoxyribonucleic Acid (DNA) and molecular biology has been figured out through Bioinformatics study. Therefore, this paper reports the performance evaluation of parallel Smith-Waterman Algorithm implementation on the new NVIDIA GeForce GTX Titan X Graphic Processing Unit (GPU) compared to the Central Processing Unit (CPU) running on Intel® CoreTM i5-4440S CPU 2.80GHz. Both of the design were developed using C-programming language and targeted to the respective platform. The code for GPU was developed and compiled using NVIDIA Compute Unified Device Architecture (CUDA). It clearly recorded that, the performance of GPU based computational is better compared to the CPU based. These results indicate that the GPU based DNA sequence alignment has a better speed in accelerating the computational process of DNA sequence alignment.
A Survey on MANETs: Architecture, Evolution, Applications, Security Issues and Solutions Burhan Ul Islam; Rashidah Funke Olanrewaju; Farhat Anwar; Athaur Rahman Najeeb; Mashkuri Yaacob
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp832-842

Abstract

Mobile ad hoc networks or MANETs, also referred to as mobile mesh networks at times, are self-configuring networks of mobile devices that are joined using wireless channels. These represent convoluted distributed systems comprising of wireless mobile nodes which are free to move and self-organise dynamically into temporary and arbitrary, ad hoc topologies. This makes it possible for devices as well as people to internetwork seamlessly in such regions that have no communication infrastructure in place. Conventionally, the single communication networking application following the ad hoc concept had been tactical networks. Lately, new technologies have been introduced such as IEEE 802.11, Hyperlan and Bluetooth that are assisting in the deployment of commercial MANETs external to the military realm. Such topical evolutions infuse a new and rising interest in MANET research and development. This paper provides an overview of the dynamic domain of MANETs. It begins with the discussion on the evolution of MANETs followed by its significance in various fields. Besides, the MANETs have been analysed from the security perspective, particularly the work performed in the node misbehaviour paradigm has been elaborated.
Optimal Voltage Stability Improvement under Contingencies using Flower Pollination Algorithm and Thyristor Controlled Series Capacitor Zulkiffli Abdul Hamid; Ismail Musirin; Muhammad Amirul Adli Nan; Zulkifli Othman
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp497-504

Abstract

Recent power systems necessitate for maintaining a safe voltage stability as the number of problems such as contingencies and reactive power insufficiency are increasing. In this paper, installation and sizing of Flexible Alternating Current Transmission System (FACTS) devices have been introduced for solving the voltage stability problems under contingencies. The FACTS device to be used is Thyristor Controlled Series Capacitor (TCSC). Besides improving the voltage magnitude at all buses to a desired level, installation of TCSC at proper locations can minimize total transmission losses of the system. To conduct the sizing task, the newly developed Flower Pollination Algorithm (FPA) has been implemented as the engine for optimization. Through experimentation, the results proved that the proposed placement and sizing technique has successfully mitigated the voltage stability problems. In addition, the computation time for FPA’s convergence was tolerable with optimum results.
Analysis of Wireless Power Transfer on the inductive coupling resonant Cik Ku Haroswati Che Ku Yahaya; Syed Farid Syed Adnan; Murizah Kassim; Ruhani Ab Rahman; Mohamad Fazrul bin Rusdi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp592-599

Abstract

Wireless power transfer through inductive coupling is proposed in this paper. Based on the concept of Tesla, the circuit was designed using two parallel inductors that are mutually coupled. The designed was split into two which are transmitter part and receiver part. The circuit was simulated using proteus simulation software. The results had shown that the changes in a number of turn of the inductor coils and distance of the two resonators affecting the efficiency of the power transfer. The wireless power transfer can be described as the transmission of electrical energy from the power source to the electrical load without any current-carrying wire connecting them. Wireless power transfer is deemed to be very useful in some circumstances where connecting wires are inconvenient. Wireless power transfer problems are different from wireless telecommunications such as radio. Commonly, wireless power transfers are conducted using an inductive coupling and followed by magnetic induction characteristics. In this project, we use magnetic induction using copper wire with a different diameter. By using these different diameters of wires, we are going to see the power transfer performance of each wire. It is possible to achieve wireless power transfer up to 30 centimeters between the transmitter and the receiver with a higher number of coil's turn. As concern as it may seem, the wireless power transfer field would be in high demand for electric power to be supplied in the future.
J-slot EBG structure for SAR Reduction of Dual Band J-slot Textile Antenna Ramesh Manikonda; Rajyalakshmi Valluri; Mallikarjuna Rao Prudhivi
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp794-802

Abstract

In this article, the dual band is achieved with J-slot on rectangular Textile antenna on Jeans fabric as substrate. It resonates at the 2.4 GHz and 5.4 GHz of Wireless Body Area Network (WBAN) bands. The novel J-slot Electromagnetic Band Gap (EBG) array consists of 2x2 elements. It is used as superstrate of J-slot textile antenna for Specific Absorption Rate (SAR) reduction and gain enhancement. The Reflection coefficient and VSWR of dual band textile antenna are simulated and measured with and without human body.
Analytical Review on Graphical Formats Used in Image Steganographic Compression Roshidi Din; Osman Ghazali; Alaa Jabbar Qasim
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 2: November 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i2.pp441-446

Abstract

This paper reviews the method of classification of the types of images used in data concealment based on the perspective of the researcher’s efforts in the past decade. Therefore, all papers were analyzed and classified according to time periods. The main objective of the study is to infer the best types of images that researchers have discussed and used, several reasons will be shown in this study, which started from 2006 to 2017, through this paper the pros and the cons in the use of favourite types in the concealment of data through previous studies.

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