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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 9,174 Documents
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Resonant Configuration Topology Exploration for Inductive Link Power Transfer S. Hafiz; Zarimin Zaharudin; Sheroz Khan; Nur Shahida Binti Midi; John Tan Teng Hwang; Kushsairy Abdul Kadir; Jawad Ali Shah
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp522-530

Abstract

This paper investigates the performance of circuit topology used in wireless power applications to optimize the level of maximum efficiency. We analyse the series and the parallel resonant topologies for use in an inductive coupling link to derive power transfer efficiency expressions verified using MATLAB. We look into the two topologies into the link under resonant conditions for selectively supplying the device with power. The results are obtained analytically which are verified subsequently by MATLAB simulation. We then analyse the links to see how maximum power transfer efficiency for a given pair of coils can be achieved. The topology at a given tuning frequency is used for powering a selected resistive load. The method is presented using a given pair of coils simulated and the results agree well with the theoretical explanation and derivations.
Coordinated Control Of SFCL And SVC For Power System Transient Stability Improvement Abdelkrim Zebar; Khaled Zehar
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2015
Publisher : Institute of Advanced Engineering and Science

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

Abstract

Transient stability is the ability of the power system to maintain synchronism when subjected to a severe disturbance, such as a short circuit on a transmission line. To improve stability, inductive type superconducting fault current limiter (SFCL) and shunt FACTS Controller (SVC) can be effectively used. This paper proposes the use of combined model based SFCL and SVC for enhancing the transient stability of a multi-machine power system considering the automatic voltage regulator. The main role of the proposed combined model is to attain at the same time a flexible control of reactive power using SVC Controller and to reduce fault current using superconducting technology based SFCL. In the present work, modification of the admittance matrix method is used for modeling of SFCL; Critical Clearing Time (CCT) has been used as an index for evaluated transient stability. The transient stability is assessed by the criterion of relative rotor angles, using numerical integration method. The effectiveness of the proposed combined model is tested on the IEEE benchmarked four-machine two-area test system applied to the case of three-phase short circuit fault in one transmission line. A simulation results are presented in this document. DOI: http://dx.doi.org/10.11591/telkomnika.v13i3.7175
Power density of rectangular microstrip patch antenna arrays for 5G indoor base station Nor Adibah Ibrahim; Tharek Abd Rahman; Razali Ngah; Omar Abd Aziz; Olakunle Elijah
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1367-1374

Abstract

The fifth-generation (5G) network has been broadly investigated by many researchers. The capabilities of 5G include massive system capacity, incredibly high data rates everywhere, very low latency and the most important point is that it is exceptionally low device cost and low energy consumption. A key technology of 5G is the millimeter wave operating at 28 GHz and 38 GHz frequency bands which enable massive MIMO and small cell base station densification. However, there has been public concern associated with human exposure to electromagnetic fields (EMF) from 5G communication devices. Hence, this paper studies the power density of a 5G antenna array that can be used for the indoor base station. The power density is the amount of power or signal strength absorbed by a receiver such as the human body located a distance from the base station. To achieve this, the design of array antennas using CST software at 28 GHz, fabrication and measurement were carried out in an indoor and hallway environment. The measurement processes were set up at IC5G at UTM Kuala Lumpur in which the distance of the transmitter to receiver where 1 m, 4 m, 8 m, and 10 m. In this study, the measured power density is found to be below the set limit by ICNIRP and hence no health implication is feared. Regardless, sufficient act of cautionary has to be applied by those staying close to small cell base stations and more studies are still needed to ensure the safety of use of 5G base stations.
A Miniaturized 878 MHz Slotted Meander Line Monopole Antenna Nabilah Ripin; Ahmad Asari Sulaiman; Nur Emileen Abd Rashid; Mohamad Fahmi Hussin; Nor Najwa Ismail
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i1.pp170-177

Abstract

A slotted meander line printed monopole antenna for low frequency applications at 878 MHz is presented. The operating frequency of the conventional printed monopole antenna was greatly reduced by the presence of the slots and meander line which lead to the reduction of the antenna size. The size reduction up to 70% compared to the conventional reference antenna is achieved in this study. The antenna has a simple structure and small antenna size of 46.8 mm x 74 mm or 0.137????0 x 0.217????0. The antenna has been fabricated on the low-cost FR4 substrate and measured to validate the simulation performances. Measured results display that the proposed antenna produces omnidirectional radiation pattern of impedance bandwidth of 48.83 MHz and the maximum gain of -1.18 dBi.
Modelling decision support system for selection maahad tafiz center using analytical hierarchal analysis Abd R Mama Mama; Mohamad A Mohamed; Amirul F Azhar; Syarilla I A Saany; Norkhairani A Rawi; Maizan M Amin; Mohd F A Kadir; M A M Nor
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp35-40

Abstract

Today, the interest of the community to send their children to religious-based schools that is Maahad Tahfiz Center (MTC)) whether managed by Government (State or Federal), private individuals, nonprofit organization (NGO) or certain organizations is very high. The demand that exceeds this offer has seen the growth of MTC rapidly. This situation provides many choices and advantages to parents. However, there is anxiety among parents to choose the MTC that fulfills the features that they want.  Hence modeling decision support system (DSS) in a MTC selection has been modeled using Analytical Hierarchy Process (AHP) provides the effective way for parents to select appropriate MTC. AHP is an effective tool for dealing with the complex decision making and aid the parents to set priorities and provide the best decision in selection MTC. Hopefully by using this model and future development of this model will help the parents make the best choices of MTC based on their preferences. 
Pornography Addiction Detection based on Neurophysiological Computational Approach Norhaslinda Kamaruddin; Abdul Wahab Abdul Rahman; Dini Handiyani
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.pp138-145

Abstract

The rise of Internet access, social media and availability of smart phones intensify the epidemic of pornography addiction especially among younger teenagers. Such scenario may offer many side effects to the individual such as alteration of the behavior, changes in moral value and rejection to normal community convention. Hence, it is imperative to detect pornography addiction as early as possible. In this paper, a method of using brain signal from frontal area captured using EEG is proposed to detect whether the participant may have porn addiction or otherwise. It acts as a complementary approach to common psychological questionnaire. Experimental results show that the addicted participants had low alpha waves activity in the frontal brain region compared to non-addicted participants. It can be observed using power spectra computed using Low Resolution Electromagnetic Tomography (LORETA). The theta band also show there is disparity between addicted and non-addicted. However, the distinction is not as obvious as alpha band. Subsequently, more work need to be conducted to further test the validity of the hypothesis. It is envisaged that with more participants and further investigation, the proposed method will be the initial step to groundbreaking way of understanding the way porn addiction affects the brain.
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.
A Survey on Software Estimation Techniques in Traditional and Agile Development Models B. Prakash; V. Viswanathan
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v7.i3.pp867-876

Abstract

Software projects mostly exceeds budget, delivered late and does not meet with the customer’s satisfaction for years. In the past, many traditional development models like waterfall, spiral, iterative, and prototyping methods are used to build the software systems. In recent years, agile models are widely used in developing the software products. The major reasons are – simplicity, incorporating the requirement changes at any time, light-weight approach and delivering the working product early and in short duration. Whatever the development model used, it still remains a challenge for software engineer’s to accurately estimate the size, effort and the time required for developing the software system. This survey focuses on the existing estimation models used in traditional as well in agile software development.
Optimum Enhance Time of Use (ETOU) for Demand Side Electricity Pricing in Regulated Market: An Implementation Using Evolutionary Algorithm M. F. Sulaima; N. Y. Dahlan; Z.M. Yasin; N.A.M. Asari; Z.H. Bohari
Indonesian Journal of Electrical Engineering and Computer Science Vol 8, No 1: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v8.i1.pp253-261

Abstract

The energy growth in Malaysia is rapidly increasing as the country moves forward with the advancement of industrial revolution. Peak hours require more energy generation, thus cost is also more expensive than during off-peak. Due to this reason, Demand Side Management (DSM) through Demand Response (DR) technique is introduced to modify the demand profile by implementing different strategies of measures. The objective of this study is to optimize the energy profile for commercial sector, as well as analyse the significance of electricity cost reduction by using the optimization technique. A Meta-heuristic technique called as Evolutionary Algorithm (EA) has been implemented in this study to optimize the load profile of a commercial installation. Significant testing shows that the proposed optimization technique has the ability to reform the Maximum Demand from peak zone to off-peak zone to reduce electricity cost. The test results have been validated through 4 cases, which are conventional method for C1 ETOU, C2 ETOU, and C1 ETOU with Optimization technique, and C2 ETOU with optimization technique tariff, respectively. The impact of the EP has been analysed, while the performance of six-time segmentation of C1 and C2 ETOU tariff indicate that the electricity cost for the medium voltage of installation has been reduced. It is hoped that the results from this study can benefit consumers by giving them the flexibility to rearrange their own energy consumption profile, so that the demand side will enjoy significant reduction of electricity cost in the future. 
Computer aided system for lymphoblast classification to detect acute lymphoblastic leukemia Syadia Nabilah Mohd Safuan; Mohd Razali Md Tomari; Wan Nurshazwani Wan Zakaria; Mohd Norzali Haji Mohd; Nor Surayahani Suriani
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 2: May 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i2.pp597-607

Abstract

Acute lymphoblastic leukemia (ALL) is a disease that is detected by the presence of lymphoblast cell. Basically, lymphoblast cell is the abnormal cell of lymphocyte which is one of the White Blood Cell (WBC) types. Early prevention is suggested as this disease can be fatal and caused death. Traditionally, ALL is detected by using manual analysis which is challenging and time consuming. It can also yield inaccurate result as it is highly dependent on the pathologist’s skills. Industry has come out with hematology counter which is fast, accurate and automated. However, these machines are costly and cannot be afforded by some countries. For that reason, Computer Aided System (CAS) will be a great help to the pathologist for assisting purposes and it also can act as second opinion for the pathologist. This system contains six main steps which are color space correction, WBC segmentation, post processing, clumped area extraction, feature extraction and lymphoblast classification. Firstly, color space correction is apply by using l*a*b* color space to standardize the image’s intensity. Next, WBC segmentation is made to prune out WBC region using color space analysis with Otsu thresholding. However, segmented image contains noises that need to be eliminated and it is accomplished by applying morphological filter with Connected Component Labelling (CCL). There is an overlapping WBC which need to be separated by using Watershed method to extract the individual cells. Next, feature extraction is made to collect the cell’s data to be fed into the classifier. Classifier used in this system to classify lymphoblast is Support Vector Machine (SVM) and this system is able to achieve 96.69% of accuracy.

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