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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 9,199 Documents
 91   92   93   94   95 
Components of Participatory Engagement within E-Learning Community Noor Hida Natrah Aziz; Haryani Haron; Afdallyna Fathiyah Harun
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.pp556-561

Abstract

This paper explores the components of participatory engagement to improve learner’s engagement within the e-learning community. Data are gathered through observations to measuring the interactions of the learner’s. The measurement included the learners’ feedbacks through the interactions of learners and educators, learners and learners and learners and content. Follow-up interviews are conducted to get deeper insights into the interactions and overall learner’s engagement environment. Findings show that in order to promote learners’ engagement in e-learning components such as accessibility, mobility, active learning and collaboration must be present in an e-learning ecosystem.
Synthesis of Germanium Dioxide Microclusters on Silicon Substrate in Non-aqueous Solution by Electrochemical Deposition Mastura Shafinaz Zainal Abidin; Shahjahan Shahjahan; Abdul Manaf Hashim
Indonesian Journal of Electrical Engineering and Computer Science Vol 6, No 1: April 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v6.i1.pp193-199

Abstract

We report the formation of crystalline germanium dioxide (GeO2) microclusters on n-Si (100) electrodeposited in non-aqueous electrolyte (a mixture of 5 vol.% germanium tetrachloride (GeCl4) and dipropylene glycol (C6H14O3) ) at current density of 20 mA/cm2 for 200 sec. Pt, C and Ge are used as an anode while Si acts as a cathode. Field- emission scanning electron microscopy (FESEM) images show that the deposited GeO2 microclusters are having rounded-mushroom-shaped particles with the smallest size of 660 nm. Energy dispersive x-ray (EDX) spectra reveal that the particles are only composed of Ge and O elements. Raman spectra confirm the formation of crystalline GeO2 with trigonal bonding structures in all samples. The photoluminescence (PL) spectra show two significant emission peaks in visible range at 2.27 eV and 2.96 eV, which seems to be attributed by GeO2 and Si defects. C6H14O3 seems to contribute to the formation of GeO2 due to its hygroscopic nature. Such microcluster structures shall provide some potential applications for electronic and optical devices on Si platform.
Fault location identification of double circuit transmission line using discrete wavelet transform Abdul Hadi Bin Mustapha; R Hamdan; F. H. Mohd Noh; N. A. Zambri; M. H. A. Jalil; Marlia Morsin; M.F. Basar
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i3.pp1356-1365

Abstract

The importance of supplying undisturbed electricity keep increasing due to modernization and lifestyle. Any disturbance in the power system may lead to discontinuation and degradation in the power quality. Therefore, detecting fault, fault type and fault location is a major issue in power transmission system in order to ensure reliable power delivery system. This paper will compare two prominent methods to estimate the fault location of double circuit transmission line. Those methods are Discrete Wavelet Transform algorithm and Fast Fourier Transform algorithm. Simulations has been carried out in MATLAB/Simulink and a variety of fault has been imposed in order to analyse the capability and accuracy of the fault location detection algorithm. Results obtained portrayed that both algorithms provide good performance in estimating the fault location. However, the maximum percentage error produced by the Discrete Wavelet Transform is only 0.25%, 0.6% lower than maximum error produces by Fast Fourier Transform algorithm. As a conclusion, Discrete Wavelet Transform possesses better capability to estimate fault location as compared to Fast Fourier Transform algorithm.
City Heating Network Dispatching and Management Information System YAO XiaoFeng; ZHAO Rui; XU HuiPu
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 4: August 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, the underlying control network was built up in view of the actual operation of heating network through applying the intelligent nodes based on CAN bus, and the data acquisition and control functions were completed to realize the local intelligent control, then adapt the change of outdoor temperature and the operating condition of heating network, and achieve the unattended purpose ultimately. The seamless connection between the underlying control network (CAN network) and the upper management network (Internet) was implemented by using embedded network gateway and reliable VPN technology,  the operating parameters of the heat exchange stations can be remote monitored in real-time. the function configuration of the underlying intelligent nodes   were achieved combines with the needs of the industrial field to realize the automatic control of the thermal parameters, software framework was put up based on FIX monitoring software to complete the module design such as graphical interface, real-time database, history data trends and reports design etc. The system has the characters such as great flexibility, simple human-machine interface, stable and reliable in practical application, which has broad applicability and be worth popularizing. DOI: http://dx.doi.org/10.11591/telkomnika.v10i4.1206
Ensemble of Differential Equations using Pareto Optimal for Traffic Forecasting Bin Yang; Yuehui Chen; Mingyan Jiang
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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

Abstract

The formal and empirical proof is that the ensemble of the learning models performs better than the single one. In order to construct the ensemble of the system of ordinary differential equations (ODEs), the two problems (diversity and accuracy of ODEs) are considered. In the paper, we estimate experimentally the model ensemble using multi-objective optimization. This paper presents a pareto optimal approach for identifying a family of the additive tree models which are used to reconstruct and identify the system of ordinary differential equations to predict the small-time scale traffic measurements data. We employ the tree-structure based evolution algorithm and particle swarm optimization (PSO) to evolve the architecture and the parameters of the additive tree model. The small-scale traffic measurements data is used to test ODE ensemble, and experimental results reveal that the proposed method is feasible and efficient for forecasting the time series. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.2878
Feature Extraction and Classification of Electric Power Equipment Images based on Corner Invariant Moments Zhai Xueming; Zhang Dongya; Dewen Wang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Feature extraction and accurate classification of electric power equipment, help to improve the automation and intelligent level of power system management. Aiming at the problems that applying Hu invariant moments to extract image feature computes large and applying corner vector to match has too dimensions, this paper presented Harris corner invariant moments algorithm. This algorithm only calculates corner coordinates other than the entire image coordinates, so can change the point feature into feature vectors, and reduce the corner matching dimensions. Combined with the SVM (Support Vector Machine) classification method, we conducted a classification for a large number of electrical equipment images, and the result shows that using Harris corner invariant moments algorithm to extract invariant moments, and classifying by these invariant moments can achieve better classification accuracy. DOI : http://dx.doi.org/10.11591/telkomnika.v12i6.1422
Research on OSNR and BER of 40G DWDM system on DRZ FENG Xiancheng; LI Xiaopeng; SI Qinghua
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: February 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

The signal modulation format is a key issue for 40 G DWDM fiber optical communication system , which determines transmission quality and spectral efficiency. Firstly, 他he scheme of key technologies and modulation format (ODB, CSRZ, DRZ, DPSK, DQPSK) of 40G DWDM system is introduced. Through the Q value with OSNR and BER, the theoretical curve between OSNR and BER is given. And then it proposes optical interface parameters requirements of 40G DWDM system. By way of adopting VOA compensation in experimental system,OTU typical spectrum,eye diagram,BER and OSNR performances have been tested and analyzed. Experiment results show that DRZ code have better transmission performance, are suitable for long or middle distance transmission, meet the demand of commercial application. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.2058
Design and Implementation of Next Generation Automotive Theft Preventive System K. Hema; Muralidharan Muralidharan
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 1: January 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i1.pp118-122

Abstract

In this paper, we proposed to design a next-generation auto theft prevention system by adding significant enhancements and modernizing the existing security features. As vehicles turn out to be more refined, vehicle security frameworks must be more grounded than at any other time. A current vehicle uses remote keyless passage framework and Immobilizer framework as the primary weaponry against vehicle robbery. These structures avoid unapproved access of the vehicle to a particular degree, however, are not a secure one. Because of the straightforward and imperfect nature of these security frameworks, auto burglary occurrences worldwide are on the ascent. This venture needs a low power microcontroller however with elite prerequisites. LPC11C14 from NXP Semiconductors addresses these issues and in this manner picked as the primary MCU. It is an ultra-low-power ARM Cortex-M0 based microcontroller that can run up to 50MHz. It has 32KB of Flash memory and 8KB RAM. 
Congestion control in vehicular adhoc network: a survey Shamsul Jamel Elias; Shahirah Mohamed Hatim; Mohamad Yusof Darus; Shapina Abdullah; Jamaluddin Jasmis; R. Badlishah Ahmad; Adam Wong Yoon Khang
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp1280-1285

Abstract

Vehicular adhoc network (VANET) has a significant potential in reducing traffic congestion to provide a stress-free and safer platform for road drivers to travel on the road. However, the current VANET is vulnerable to several challenges which need to be overcome. Congestion control is considered as one of the main challenges in VANET due to the high dynamic topology characteristic. Reliable congestion control (CC) are necessary to provide effectient dissemination of time-critical safety messages in VANET applications; safety and non-safety applications. In this paper, we present the overview on VANET, its application and challenges. We also discuss on the congestion control and provide a brief survey on the congestion control algorithms such as vehicular cloud computing, multiplicative rate decreasing algorithm, multi-objective Tabu search, D-FPAV algorithm and beaconing strategies which have been proposed in order to provide better solutions towards achieving a successful Smart Tranporation System.
Two-step Classification Algorithm Based on Decision-Theoretic Rough Set Theory Jun Wang; Yulong Xu; Weidong Yu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 7: July 2013
Publisher : Institute of Advanced Engineering and Science

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

Abstract

This paper introduces rough set theory and decision-theoretic rough set theory. Then based on the latter, a two-step classification algorithm is proposed. Compared with primitive DTRST algorithms, our method decreases the range of negative domain and employs a two-steps strategy in classification. New samples and unknown samples can be estimated whether it belongs to the negative domain when they are found. Then, fewer wrong samples will be classified in negative domain. Therefore, error rate and loss of classification is lowered. Compared with traditional information filtering methods, such as Naive Bayes algorithm and primitive DTRST algorithm, the proposed method can gain high accuracy and low loss. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2802 

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