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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Teddy Surya Gunawan
International Islamic University Malaysia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Penetration Testing using Kali Linux: SQL Injection, XSS, Wordpres, and WPA2 Attacks Teddy Surya Gunawan; Muhammad Kasim Lim; Mira Kartiwi; Noreha Abdul Malik; Nanang Ismail
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.pp729-737

Abstract

Nowadays, computers, smart phones, smart watches, printers, projectors, washing machines, fridges, and other mobile devices connected to Internet are exposed to various threats and exploits. Of the various attacks, SQL injection, cross site scripting, Wordpress, and WPA2 attack were the most popular security attacks and will be further investigated in this paper. Kali Linux provides a great platform and medium in learning various types of exploits and peneteration testing. All the simulated attack will be conducted using Kali Linux installed on virtual machine in a compuer with Intel Core i5 and 8 GB RAM, while the victim’s machine is the host computer which run Windows 10 version 1709. Results showed that the attacks launched both on web and firewall were conducted successfully.
Comparison of Entropy Coding mechanism on IEEE1857.2 Lossless Audio Compression Standard Fathiah Abdul Muin; Teddy Surya Gunawan; Mira Kartiwi; Elsheikh M.A. Elsheikh
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp176-183

Abstract

This paper has two objectives. First, we aim to review and analyze the performance of the IEEE 1857.2 standard, focusing is on the Golomb-Rice and Arithmetic entropy algorithms as well as the effect of the pre-processing block on these entropy blocks. The pre-processing block normalizes the error residue of the Linear Predictive encoder, which then is passed to Entropy block, where the selector chooses the entropy encoder to use. The second objective is to present results from experimenting different existing algorithms available to benchmark it’. The results are discussed, and comparisons are made to identify the effect on compression ratio and encoding speed of the lossless encoder. As well as this, comparison is made to analyze effects of enabling and disabling the pre-processing output to the Entropy Coding block. We concluded that pre-processing block works well to flatten the output at lower predictor order for all the sound types, but works best at improving the residual output for music sound type.
Measuring the Road Traffic Intensity using Neural Network with Computer Vision Muhammad Hamdan; Othman Omran Khalifah; Teddy Surya Gunawan
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp184-190

Abstract

Traffic congestion plagues all driver around the world. To solve this problem computer vision can be used as a tool to develop alternative routes and eliminate traffic congestions. In the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT) this solution will have a greater impact on current systems. In this paper, the Macroscopic Urban Traffic model is used using computer vision as its source and traffic intensity monitoring system is implemented. The input of this program is extracted from a traffic surveillance camera and another program running a neural network classification which can classify and distinguish the vehicle type is on the road. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated.
On the Comparison of Line Spectral Frequencies and Mel-Frequency Cepstral Coefficients Using Feedforward Neural Network for Language Identification Teddy Surya Gunawan; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp168-175

Abstract

Of the many audio features available, this paper focuses on the comparison of two most popular features, i.e. line spectral frequencies (LSF) and Mel-Frequency Cepstral Coefficients. We trained a feedforward neural network with various hidden layers and number of hidden nodes to identify five different languages, i.e. Arabic, Chinese, English, Korean, and Malay. LSF, MFCC, and combination of both features were extracted as the feature vectors. Systematic experiments have been conducted to find the optimum parameters, i.e. sampling frequency, frame size, model order, and structure of neural network. The recognition rate per frame was converted to recognition rate per audio file using majority voting. On average, the recognition rate for LSF, MFCC, and combination of both features are 96%, 92%, and 96%, respectively. Therefore, LSF is the most suitable features to be utilized for language identification using feedforward neural network classifier.
Performance Evaluation of Multichannel Audio Compression Teddy Surya Gunawan; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 1: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v10.i1.pp146-153

Abstract

In recent years, multichannel audio systems are widely used in modern sound devices as it can provide more realistic and engaging experience to the listener. This paper focuses on the performance evaluation of three lossy, i.e. AAC, Ogg Vorbis, and Opus, and three lossless compression, i.e. FLAC, TrueAudio, and WavPack, for multichannel audio signals, including stereo, 5.1 and 7.1 channels. Experiments were conducted on the same three audio files but with different channel configurations. The performance of each encoder was evaluated based on its encoding time (averaged over 100 times), data reduction, and audio quality. Usually, there is always a trade-off between the three metrics. To simplify the evaluation, a new integrated performance metric was proposed that combines all the three performance metrics. Using the new measure, FLAC was found to be the best lossless compression, while Ogg Vorbis and Opus were found to be the best for lossy compression depends on the channel configuration. This result could be used in determining the proper audio format for multichannel audio systems.
Speech Enhancement based on Wiener Filter and Compressive Sensing Amart Sulong; Teddy Surya Gunawan; Othman O. Khalifa; Mira Kartiwi; Eliathamby Ambikairajah
Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 2: May 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v2.i2.pp367-379

Abstract

In the last few decades, many advanced technologies have been proposed, in which communications played a great role as well as telecommunications applications. The noise elimination in various environments became the most concerned as it greatly hindered the speech communication applications. The improvement of noisy speech interms of quality and intelligibility are taken into account without introducingany additional noise. Many speech enhancement algorithms have been proposed. Wiener filter is one of the classical algorithm that improve the noisy speech by reducing its noise components through selectively chosen Wiener gain. In this paper, compressive sensing method by randomize measurement matrix is combined with the Wiener filter to reduce the noisy speech signal to produce high signal to noise ratio. The PESQ is used to measure the quality of the proposed algorithm design. Experimental results showthe effectiveness of our proposed algorithm to enhance noisy signals corrupted by various noises compared to other traditional algorithms, in which high PESQ scores were achieved across various noises and different SNRs.
Development of Efficient Iris Identification Algorithm using Wavelet Packets for Smartphone Application Teddy Surya Gunawan; Nurul Shaieda Solihin; Malik Arman Morshidi; Mira Kartiwi
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 2: November 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i2.pp450-456

Abstract

Nowadays, iris recognition is widely used for personal identification and verification based on biometrical technology, especially in the smartphone arena. By having this iris recognition for identification and verification, the smartphone will be secured since every person have their own iris type. In this paper, we proposed an efficient iris recognition using Wavelet Packets and Hamming distance which has lightweight computational requirements while maintaining the accuracy. There are several steps needed in order to recognize the iris which are pre-processing the iris image consists of segmentation and normalization, extract the feature that available in the iris image and identify this image to see whether it match with the person or not. For comparison purposes, different types of wavelet bases will be compared, including symlets, discrete meyer, biorthogonals, daubechies, and coiflets. Performance of the proposed algorithm was tested on Chinese Academy of Sciences Institute of Automation (CASIA) iris image database. The optimum wavelet basis function obtained is symlet. Results showed that the accuracy of the proposed algorithm is 100% identification rate.
Development of Quran Reciter Identification System Using MFCC and Neural Network Tayseer Mohammed Hasan Asda; Teddy Surya Gunawan; Mira Kartiwi; Hasmah Mansor
Indonesian Journal of Electrical Engineering and Computer Science Vol 1, No 1: January 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v1.i1.pp168-175

Abstract

Currently, the Quran is recited by so many reciters with different ways and voices.  Some people like to listen to this reciter and others like to listen to other reciters. Sometimes we hear a very nice recitation of al-Quran and want to know who the reciter is. Therefore, this paper is about  the development of Quran reciter recognition and identification system based on Mel Frequency Cepstral Coefficient (MFCC) feature extraction and artificial neural network (ANN). From every speech, characteristics from the utterances will be extracted through neural network model. In this paper a database of five Quran reciters is created and used in training and testing. The feature vector will be fed into Neural Network back propagation learning algorithm for training and identification processes of different speakers. Consequently,  91.2%  of the successful match between targets and input occurred with certain number of hidden layers  which shows how efficient are Mel Frequency Cepstral Coefficient (MFCC) feature extraction  and artificial neural network (ANN) in identifying the reciter voice perfectly.
On the Use of Edge Features and Exponential Decaying Number of Nodes in the Hidden Layers for Handwritten Signature Recognition Teddy Surya Gunawan; Mira Kartiwi
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.pp722-728

Abstract

Handwritten signatures are playing an important role in finance, banking and education and more because it is considered the “seal of approval” and remains the most preferred means of authentication. In this paper, an offline handwritten signature authentication algorithm is proposed using the edge features and deep feedforward neural network (DFNN). The number of hidden layers in DFNN is configured to be at least one layer and more. In this paper, an exponential decaying number of nodes in the hidden layers was proposed to achieve better recognition rate with reasonable training time. Of the six edge algorithms evaluated, Roberts operator and Canny edge detectors were found to produce better recognition rate. Results showed that the proposed exponential decaying number of nodes in the hidden layers outperform other structure. However, more training data was required so that the proposed DFNN structure could have more efficient learning.
Robust Control of Bench-top Helicopter Using Quantitative Feedback Theory Ameerul Hakeem Mohd Hairon; Hasmah Mansor; Teddy Surya Gunawan; Sheroz Khan
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A three degree of freedom (3-DOF) bench-top helicopter is a simplified aerial vehicle which is used to study the behaviors of the helicopter as well as testing multiple flight control approaches for their efficiency. Designing helicopter’s dynamic control is a challenging task due to the presence of high uncertainties and non-linear behavior. In this study, Quantitative Feedback Theory (QFT) is proposed to achieve robust control over the helicopter model. It utilizes frequency domain methodology which ensures plant’s stability by considering the feedback of the system and thus removing the effect of disturbances and reducing sensitivity of parameter’s variation. The proposed technique is tested against LQR-tuned PID controller to demonstrate its procedures as well as its performance. Simulation results obtained through MATLAB Simulink software shown us that QFT algorithm managed to reduce percentage of overshoot and settling time about 50% and 30% respectively over the classical PID controller. DOI: http://dx.doi.org/10.11591/telkomnika.v14i3.7899
Co-Authors Ali Aboadla Ali Aryo Bawono Ali Sophian Amart Sulong Ameerul Hakeem Mohd Hairon Amir Akramin Shafie Arselan Ashraf Belal A. Hamida Bob Subhan Riza Dmitry Vedenyapin Edy Victor Haryanto Edy Victor Haryanto, Edy Victor Eliathamby Ambikairajah Elsheikh M.A. Elsheikh Erwin Sulaemen Ezzidin Hassan Aboadla Farah Diyana Abdul Rahman Fathiah Abdul Muin Hasmah Mansor Intan Rahmithul Husna Yaldi Malik Arman Morshidi Mashkuri Bin Yaacob Mimi Aminah binti Wan Nordin Mira Kartiwi Mira Kartiwi Mohamed H. Habaebi Mohd Azmi Omar Muhammad Fahreza Alghifari Muhammad Hamdan Muhammad Hamdan Hasan Gani Muhammad Kasim Lim Muhammad Kassim Lim Nanang Ismail Noreha Abdul Malik Norfarah Nadia Ismail Nur Atikah Muhamat Saleh Nurul Fariza Zulkurnain Nurul Shaieda Solihin Othman O. Khalifa Othman Omran Khalifah Rika Rosnelly Sheroz Khan Syed Asif Ahmad Qadri Tayseer Mohammed Hasan Asda Tika Arundina Wan Athereah Yahya Yasmin Mahira Saiful Munir Zuriati Janin