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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 65 Documents
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Search results for , issue "Vol 18, No 3: June 2020" : 65 Documents clear
Internet of things: security requirements, attacks and counter measures Maria Imdad; Deden Witarsyah Jacob; Hairulnizam Mahdin; Zirawani Baharum; Shazlyn Milleana Shaharudin; Mohd Sanusi Azmi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1520-1530

Abstract

Internet of Things (IoT) is a network of connected and communicating nodes. Recent developments in IoT have led to advancements like smart home, industrial IoT and smart healthcare etc. This smart life did bring security challenges along with numerous benefits. Monitoring and control in IoT is done using smart phone and web browsers easily.  There are different attacks being launched on IoT layers on daily basis and to ensure system security there are seven basic security requirements which must be met. Here we have used these requirements for classification and subdivided them on the basis of attacks, followed by degree of their severity, affected system components and respective countermeasures. This work will not only give guidelines regarding detection and removal of attacks but will also highlight the impact of these attacks on system, which will be a decision point to safeguard  system from high impact attacks on priority basis.
Cyberbullying identification in twitter using support vector machine and information gain based feature selection Ni Made Gita Dwi Purnamasari; M. Ali Fauzi; Indriati Indriati; Liana Shinta Dewi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1494-1500

Abstract

Cyberbullying is one of the actions that violate the ITE Law where the crime is committed on social media applications such as Twitter. This action is difficult to detect if no one is reporting the tweet. Cyberbullying tweet identification aims to classify tweets that contain bullying. Classification is done using Support Vector Machine method where this method aims to find the dividing hyperplane between negative and positive class. This study is a text classification where more data is used, the more features are produced, therefore this research also uses Information Gain as feature selection to select features that are not relevant to the classification. The process of the system starts from text preprocessing with tokenizing, filtering, stemming and term weighting. Then perform the information gain feature selection by calculating the entropy value of each term. After that perform the classification process based on the terms that have been selected, and the output of the system is identification whether the tweet is bullying or not. The result of using SVM method is accuracy 75%, precision 70.27%, recall 86.66% and f-measure 77.61% on experiment maximum iteration = 20, λ = 0.5, γ = 0.001, ε = 0.000001, and C = 1. The best threshold of information gain is 90%, with accuracy 76.66%, precision 72.22%, recall 86.66% and f-measure 78.78%.
Single-pump multiwavelength hybrid raman-EDF laser using a non-adiabatic microfiber interferometer Muhammad Faiz Ibrahim; Nani Fadzlina Naim; Mas Izyani Bt Md Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1446-1453

Abstract

This paper presents a multiwavelength fiber laser utilizing non-adiabatic tapered EDF based Mach Zehnder Interferometer (MZI) in hybrid Raman-EDF gains design with a linear cavity. A stable laser was obtained from the single pump with a 1497 nm wavelength through the employment of a 20:80 optical circulators and 99% reflective mirror. The generated backward propagating oscillates inside the laser cavity generate the stable multiwavelength output with 4 channels, which is coupled out via the 10:90 coupler and the output laser is characterized using an OSA with a resolution of 0.015 nm. The hybrid Raman-EDF gain is pumped from the external cavity by a Raman Pump Unit (RPU) and produced a stable multiwavelength laser output with SMSR of 28.9 dBm for 300 mW pump power, 30.7 dBm for 1000 mW pump power and 33.7 dBm for 1500 mW pump power.
Characterising and detection of botnet in P2P network for UDP protocol Noor Zuraidin Mohd Safar; Noryusliza Abdullah; Hazalila Kamaludin; Suhaimi Abd Ishak; Mohd Rizal Mohd Isa
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1584-1595

Abstract

Developments in computer networking have raised concerns of the associated Botnets threat to the Internet security. Botnet is an inter-connected computers or nodes that infected with malicious software and being controlled as a group without any permission of the computer’s owner. This paper explores how network traffic characterising can be used for identification of botnet at local networks. To analyse the characteristic, behaviour or pattern of the botnet in the network traffic, a proper network analysing tools is needed. Several network analysis tools available today are used for the analysis process of the network traffic. In the analysis phase, the botnet detection strategy based on the signature and DNS anomaly approach are selected to identify the behaviour and the characteristic of the botnet. In anomaly approach most of the behavioural and characteristic identification of the botnet is done by comparing between the normal and anomalous traffic. The main focus of the network analysis is studied on UDP protocol network traffic. Based on the analysis of the network traffic, the following anomalies are identified, anomalous DNS packet request, the NetBIOS attack, anomalous DNS MX query, DNS amplification attack and UDP flood attack. This study, identify significant Botnet characteristic in local network traffic for UDP network as additional approach for Botnet detection mechanism.
Cyclic voltammetry characterization analysis on the cu/flame retardant 4 fabricated biosensor Irni Hamiza Hamzah; Azman Ab Malik; Aida Zulia Zulhanip; Zainal Hisham Che Soh; Alhan Farhanah Abd Rahim
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1199-1206

Abstract

Silicon, glass and ceramic are commonly base substrate used in DNA biosensor fabrication due to its biocompatible, expensive, hard and brittle. However due to the difficulty for drilling and dicing, these materials required expensive equipments and complex methodology of fabrication. Large gap of thermal expansion coefficient (TEC) between silicon/glass and film caused microcracks. Hence, the aim of this work is to investigate the suitability and the application of a non-biocompatible material, flame retardant 4 (FR4) as a base substrate for a label free DNA biosensor. Cyclic voltammetry (CV) reversible method has been implemented to test the fabricated Cu/Au on the FR4. It is found that the fabrication of Au has been made possible by the used of oxide-free Cu as an adhesion layer on the FR4 substrate. The area size of counter electrode (CE), working electrode (WE) and reference electrode (RE) are found to be 6.25 mm2, 0.581 mm2 and 1.04 mm2, respectively, in order to achieve the unity reversible redox relationship and to ensure the sensor’s reliability for 10 mM K3Fe(CN)6 solution in 0.1 M KCl. Thus it can be concluded that the proposed FR4-based substrate fulfilled the CV reversible process characterization.
Graphene derivative coated QCM-based gas sensor for volatile organic compound (VOC) detection at room temperature Monika Gupta; Nurul Athirah; Huzein Fahmi Hawari
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1279-1286

Abstract

Volatile organic compounds (VOCs) affect our daily life through their emission from very common sources such as plants, building materials, paints, pesticides, and fossil fuel burning. The detection of VOCs at room temperature is a prime requirement. The graphene-based gas sensor has the potential to detect these VOC gases due to its attractive features such as high mobility and large surface area. In this work, a graphene-derivative is prepared as a sensing material in order to detect acetone. The thin film of graphene-derivative is prepared by a drop-cast method on a quartz crystal microbalance (QCM) sensor followed by drying in the room environment conditions. The prepared graphene-derivative and thin films are characterized structurally and morphologically by standard microscopic techniques such as FESEM, EDX, and Raman spectroscopy. The electrical parameters such as mobility and resistivity are measured using Hall-effect measurements at room temperature. The response and recovery time of the graphene-derivative based 10 MHz QCM sensor are found to be 23 s and 20 s, respectively. This highly sensitive graphene-based gas sensor with good reversibility can be employed for human health and environment safety applications. 
Single identity in check-in using NFC in airport Mikhael Bagus Renardi; Noor Cholis Basjaruddin; Kuspriyanto Kuspriyanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1629-1637

Abstract

An increase in transactions in airports is in line with a growing number of airline passengers, thus, a system which can enhance the service may be required. One of the concerns related to airline services is the long time for transactions due to the time required for each transaction and the number of transactions for each passenger. One of the transactions which require long time is the check-in process. In addition, the conventional check-in process also requires paper which its use is rapidly rising due to the increasing number of passengers. Hence, an NFC (Near Field Communication)-based system can be applied to accelerate transactions and to reduce the use of paper. Transactions in airports require several documents including booking reference and passengers’ identity cards, and both of which can be digitally stored in an NFC device. This study revealed that the implementation of SI could accommodate the check-in process in airports and decrease the redudancy of passenger data.
A new hyhbrid coefficient of conjugate gradient method Nur Syarafina Mohamed; Mustafa Mamat; Mohd Rivaie; Shazlyn Milleana Shaharudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1454-1463

Abstract

Hybridization is one of the popular approaches in modifying the conjugate gradient method. In this paper, a new hybrid conjugate gradient is suggested and analyzed in which the parameter is evaluated as a convex combination of  while using exact line search. The proposed method is shown to possess both sufficient descent and global convergence properties. Numerical performances show that the proposed method is promising and has overpowered other hybrid conjugate gradient methods in its number of iterations and central processing unit per time. 
A posture monitoring system with IMU for ophthalmologist while operating the slit lamp Kian Sek Tee; Eugene Low; Wellesly Tony; Safinaz Binti Mohd Khialdin; Jaysuman Bin Pusppanathan; Chin Fhong Soon; Toong Hai Sam
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1262-1269

Abstract

The posture monitoring system monitors the posture changes of the upper body and the spinal cord applying to ophthalmologists while operating the slit lamp. The motivation to the pursuit of this system is to relate posture changes while in a static sitting posture to the spinal deviation from the g-line. Often times, the spinal deviation from the g-line is classified as bad posture because of the shift in weight distribution on the spine causing pain and discomfort in certain areas of the spine. This paper presents the design concept, the development process and the working principle of the posture monitoring system using Inertial Measurement Unit (IMU) sensor. The raw measurement data obtained from human trials is tabulated and converted into a graphical representation in which all postures can be identified and distinguished by referring the relative wave pattern. The procedure is important in the improvement on the posture monitoring system for the human trials on the ophthalmologist in future.
Fault classification in smart distribution network using support vector machine Ong Wei Chuan; Nur Fadilah Ab Aziz; Zuhaila Mat Yasin; Nur Ashida Salim; Norfishah A. Wahab
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 3: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i3.pp1148-1155

Abstract

Machine learning application have been widely used in various sector as part of reducing work load and creating an automated decision making tool. This has gain the interest of power industries and utilities to apply machine learning as part of the operation. Fault identification and classification based machine learning application in power industries have gain significant accreditation due to its great capability and performance. In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. Eleven different types of faults are generated with respect to actual network. A wide range of simulation condition in terms of different fault impedance value as well as fault types are considered in training and testing data. Right setting parameters are important to learning results and generalization ability of SVM. Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. Initial finding from simulation result indicates that the proposed method is quick in learning and shows good accuracy values on faults type classification in distribution system. The developed algorithm is tested on IEEE 34 bus and IEEE 123 bus test distribution system. 

Page 4 of 7 | Total Record : 65

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