cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
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
 1   2   3   4   5 
Search results for , issue "Vol 13, No 2: February 2019" : 57 Documents clear
Thermal distribution analysis of rice weevil disinfestation using microwave heating treatment Maliki Ibrahim; Rosemizi Abd Rahim; Junita Mohd Nordin; Siti Zulaika Abdul Nyzam; Muhammad Thaqif Abdullah
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp759-765

Abstract

This paper presents an analysis of a microwave heating thermal distribution in the rice weevil disinfestation treatment. The sample of rice and rice weevil has been heated by microwave and the infrared thermal camera has been used to capture the heating distribution. The analysis of the rice and the rice weevil condition due to electromagnetic energy exposure is presented. There are three stages of the microwave heating has been taken in the analysis i.e. 10, 20, 30 seconds exposure period at 100W of energy.  Found that the treatment of rice weevil disinfestation using microwave energy is promising in the future, but needs a lot of improvement to be studied. The beauty of using microwave energy for rice weevil disinfestation is not only the rice weevil can be killed, but even its eggs or larvae inside the rice kernel will be killed before it hatches.
Allocation of distributed generation and capacitor banks in distribution system Olatunde Oladepo; Hasimah Abdul Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp437-446

Abstract

Voltage profile and power losses on the distribution system is a function of real and imaginary power loading condition. This can be effectively managed through the controlled real and reactive power flow by optimal placement of capacitor banks (CB) and distributed generators (DG). This paper presents adaptive Particle Swarm Optimization (MPSO) to efficiently tackle the problem of simultaneous allocation of DG and CB in radial distribution system to revamp voltage magnitude and reduce power losses. The modification to the conventional PSO was achieved by replacing the inertial weight equation (W) in the velocity update equation base on the particle best experience in the previous iteration. The inertial weight equation is designed to vary with respect to the iteration value in the algorithm. The proposed method was investigated on IEEE 30-bus, 33-bus and 69-bus test distribution systems. The results shows a significant improvement in the rate of convergence of APSO, improved voltage profile and loss reduction.
Wind direction sensor based on thermal anemometer for olfactory mobile robot Helmy Widyantara; Muhammad Rivai; Djoko Purwanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp475-484

Abstract

A wind direction sensor has been implemented for many applications, such as navigation, weather, and air pollution monitoring. In an odor tracking system, the wind plays the important role to carry gas from its source. Therefore, the precise, low-cost, and effective wind direction sensor is required to trace the gas source. In this study, a new design of wind direction sensor has been developed using thermal anemometer principle with the main component of the positive temperature coefficient thermistor. Three anemometers each of which has different directions are used as inputs for the neural network to determine the direction of the wind automatically.The experimental results show that the wind sensor system is able to detect twelve wind directions. A mobile robot equipped with this sensor system can navigate to a wind source in the open air with a success rate of 80%.This system is expected to increase the success rate of the mobile robot in searching for dangerous leaking gas in the open air.
Optimization of video quality via fuzzy logic base adaptive media playout Farij Ehtiba; Badlishah Ahmad; Mostafijur Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp527-533

Abstract

This paper addresses the issue of interruption of Virable Bit Rate (VBR) video streaming over IP network, due to channel quality fluctuation. Specifically, a Fuzzy Logic (FL) Control principle is fused with Adaptive Media Playout (AMP) control to estimate an appropriate playout frame rate, namely FLAMP. Based on the estimation of the playout frame rate, the FLAMP algorithm adjusts the consumption rate smoothly to avoid video stream degradation. Simulation results validate that the FLAMP scheme efficiently reduces the buffer outage probability and provides better visual quality where FLAMP gives 26.5% less ferquence of playout interruption, and 21.6% less variance of distortion of playout as compared to APTA.
An investigative design of optimum stochastic language model for bangla autocomplete Md.Iftakher Alam Eyamin; Md. Tarek Habib; Muhammad Ifte Khairul Islam; Md. Sadekur Rahman; Md. Abbas Ali Khan
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp671-676

Abstract

Word completion and word prediction are two important phenomena in typing that have extreme effect on aiding disable people and students while using keyboard or other similar devices. Such autocomplete technique also helps students significantly during learning process through constructing proper keywords during web searching. A lot of works are conducted for English language, but for Bangla, it is still very inadequate as well as the metrics used for performance computation is not rigorous yet. Bangla is one of the mostly spoken languages (3.05% of world population) and ranked as seventh among all the languages in the world. In this paper, word prediction on Bangla sentence by using stochastic, i.e. N-gram based language models are proposed for autocomplete a sentence by predicting a set of words rather than a single word, which was done in previous work. A novel approach is proposed in order to find the optimum language model based on performance metric. In addition, for finding out better performance, a large Bangla corpus of different word types is used.
A multi-instance multi-sample palmprint identification system Thulfiqar H. Mandeel; Muhammad Imran Ahmad; Said Amirul Anwar
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp825-830

Abstract

The multibiometric recognition system considered more reliable than the unimodal biometric recognition system due to the addition of an extra information that increases the discrimination between the classes. In this paper, a multi-sample multi-instance biometric recognition system is proposed. The aim of the proposed system is to increase the robustness of the identification. the proposed system also addresses the overfitting to the train samples problem of a feature extraction algorithm, named 2-Dimensional Linear Discriminant analysis (2D-LDA). The samples in the proposed method are bootstrapped and the 2D-LDA performed on each group during the offline phase. While in the online phase, the tested class will be transformed into subspaces using different eigenvectors that obtained from different samplings, and the results matched with templates in the corresponding subspace. To evaluate the proposed method, two palmprint databases are used which are IIT Delhi Touchless Palmprint Database and PolyU palmprint database, and different rank-level fusion algorithms are investigated. The results of the proposed method show improvement in the identification rate.
A study of reflection phase of reflectarray antennas with high loss organic substrates M. Y. Ismail; H. I Malik; S. R. Masrol; Sharmiza Adnan
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp773-778

Abstract

This paper presents an analysis of reflection phase of reflectarray antenna based on high loss organic substrate material. Paper substrate material derived from recycled materials was characterized for dielectric material properties. The material shows excellent dielectric material properties with permittivity of 1.63 and loss tangent of 0.048. Effect of substrate height variation over the reflection phase has been discussed. Full wave analysis of the simulated model depicts that the reduction in substrate height after a certain point results in reflection phase distortion of reflectarray element. Validation of the results has been done by simulation, fabrication and scattering parameters measurements of a rectangular patch element on proposed substrate material. The results show a broadband frequency response of 355 MHz and a phase range of 301º at a phase gradient of 0.14 º/MHz.
Convergence analysis of the unpunctured turbo trellis-coded modulation (UTTCM) Ahmed Haffane; Abdelhafid Hasni; Mustapha Khelifi; Boufeldja Kadri
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp447-452

Abstract

In this paper, the performance of the Unpunctured Turbo Trellis-Coded Modulation (UTTCM) over Additive White Gaussian Noise (AWGN) channel is analyzed using the non-binary extrinsic information transfer (EXIT) chart. The exchange of the extrinsic information between the decoder components is tracked, allowing the generation of an EXIT chart, which is a powerful tool for analyzing the convergence behavior of iterative decoding and prediction of convergence position. The Simulation results are compared with the turbo cliff positions on the BER curves.
Optical millimeter wave generation utilizing stimulated brillouin scattering for radio over fiber system M.M.H Husaini; C.B.M Rashidi; SN Azemi; S.A Aljunid; M.S Anuar
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp818-824

Abstract

Optical millimeter-wave signal generation in Radio over Fiber (RoF) based on external modulators using different modulation schemes such as Single-Sideband (SSB), Double-Sideband (DSB) are experimentally compared. The major fallout for external modulation scheme system performance to downgrade is due to dispersion and the fading effect in optical signal generation while generating high Bit Error Rate (BER) when involving long distance delivery.  In this work, we proposed mm-wave signal utilize Stimulated Brillouin Scattering (SBS) scheme which  indicates the best performance amongst the scheme based on simulation that it achieves to propagate longest of distance over fiber, highest receiver sensitivity, the lowest BER and coherence of Mach-Zehnder Modulator (MZM) extinction ratio. Mm-wave signal of 40 Ghz and 10 Gb/s data rate was generated with the plotting of eye diagram.
A dynamic K-means clustering for data mining Md. Zakir Hossain; Md.Nasim Akhtar; R.B. Ahmad; Mostafijur Rahman
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp521-526

Abstract

Data mining is the process of finding structure of data from large data sets. With this process, the decision makers can make a particular decision for further development of the real-world problems. Several data clusteringtechniques are used in data mining for finding a specific pattern of data. The K-means method isone of the familiar clustering techniques for clustering large data sets.  The K-means clustering method partitions the data set based on the assumption that the number of clusters are fixed.The main problem of this method is that if the number of clusters is to be chosen small then there is a higher probability of adding dissimilar items into the same group. On the other hand, if the number of clusters is chosen to be high, then there is a higher chance of adding similar items in the different groups. In this paper, we address this issue by proposing a new K-Means clustering algorithm. The proposed method performs data clustering dynamically. The proposed method initially calculates a threshold value as a centroid of K-Means and based on this value the number of clusters are formed. At each iteration of K-Means, if the Euclidian distance between two points is less than or equal to the threshold value, then these two data points will be in the same group. Otherwise, the proposed method will create a new cluster with the dissimilar data point. The results show that the proposed method outperforms the original K-Means method.

Page 2 of 6 | Total Record : 57

 1   2   3   4   5 

Filter by Year

2019 2019


Reset
Filter By Issues
All Issue Vol 41, No 1: January 2026 Vol 40, No 3: December 2025 Vol 40, No 2: November 2025 Vol 40, No 1: October 2025 Vol 39, No 3: September 2025 Vol 39, No 2: August 2025 Vol 39, No 1: July 2025 Vol 38, No 3: June 2025 Vol 38, No 2: May 2025 Vol 38, No 1: April 2025 Vol 37, No 3: March 2025 Vol 37, No 2: February 2025 Vol 37, No 1: January 2025 Vol 36, No 3: December 2024 Vol 36, No 2: November 2024 Vol 36, No 1: October 2024 Vol 35, No 3: September 2024 Vol 35, No 2: August 2024 Vol 35, No 1: July 2024 Vol 34, No 3: June 2024 Vol 34, No 2: May 2024 Vol 34, No 1: April 2024 Vol 33, No 3: March 2024 Vol 33, No 2: February 2024 Vol 33, No 1: January 2024 Vol 32, No 3: December 2023 Vol 32, No 1: October 2023 Vol 31, No 3: September 2023 Vol 31, No 2: August 2023 Vol 31, No 1: July 2023 Vol 30, No 3: June 2023 Vol 30, No 2: May 2023 Vol 30, No 1: April 2023 Vol 29, No 3: March 2023 Vol 29, No 2: February 2023 Vol 29, No 1: January 2023 Vol 28, No 3: December 2022 Vol 28, No 2: November 2022 Vol 28, No 1: October 2022 Vol 27, No 3: September 2022 Vol 27, No 2: August 2022 Vol 27, No 1: July 2022 Vol 26, No 3: June 2022 Vol 26, No 2: May 2022 Vol 26, No 1: April 2022 Vol 25, No 3: March 2022 Vol 25, No 2: February 2022 Vol 25, No 1: January 2022 Vol 24, No 3: December 2021 Vol 24, No 2: November 2021 Vol 24, No 1: October 2021 Vol 23, No 3: September 2021 Vol 23, No 2: August 2021 Vol 23, No 1: July 2021 Vol 22, No 3: June 2021 Vol 22, No 2: May 2021 Vol 22, No 1: April 2021 Vol 21, No 3: March 2021 Vol 21, No 2: February 2021 Vol 21, No 1: January 2021 Vol 20, No 3: December 2020 Vol 20, No 2: November 2020 Vol 20, No 1: October 2020 Vol 19, No 3: September 2020 Vol 19, No 2: August 2020 Vol 19, No 1: July 2020 Vol 18, No 3: June 2020 Vol 18, No 2: May 2020 Vol 18, No 1: April 2020 Vol 17, No 3: March 2020 Vol 17, No 2: February 2020 Vol 17, No 1: January 2020 Vol 16, No 3: December 2019 Vol 16, No 2: November 2019 Vol 16, No 1: October 2019 Vol 15, No 3: September 2019 Vol 15, No 2: August 2019 Vol 15, No 1: July 2019 Vol 14, No 3: June 2019 Vol 14, No 2: May 2019 Vol 14, No 1: April 2019 Vol 13, No 3: March 2019 Vol 13, No 2: February 2019 Vol 13, No 1: January 2019 Vol 12, No 3: December 2018 Vol 12, No 2: November 2018 Vol 12, No 1: October 2018 Vol 11, No 3: September 2018 Vol 11, No 2: August 2018 Vol 11, No 1: July 2018 Vol 10, No 3: June 2018 Vol 10, No 2: May 2018 Vol 10, No 1: April 2018 Vol 9, No 3: March 2018 Vol 9, No 2: February 2018 Vol 9, No 1: January 2018 Vol 8, No 3: December 2017 Vol 8, No 2: November 2017 Vol 8, No 1: October 2017 Vol 7, No 3: September 2017 Vol 7, No 2: August 2017 Vol 7, No 1: July 2017 Vol 6, No 3: June 2017 Vol 6, No 2: May 2017 Vol 6, No 1: April 2017 Vol 5, No 3: March 2017 Vol 5, No 2: February 2017 Vol 5, No 1: January 2017 Vol 4, No 3: December 2016 Vol 4, No 2: November 2016 Vol 4, No 1: October 2016 Vol 3, No 3: September 2016 Vol 3, No 2: August 2016 Vol 3, No 1: July 2016 Vol 2, No 3: June 2016 Vol 2, No 2: May 2016 Vol 2, No 1: April 2016 Vol 1, No 3: March 2016 Vol 1, No 2: February 2016 Vol 1, No 1: January 2016 Vol 16, No 3: December 2015 Vol 16, No 2: November 2015 Vol 16, No 1: October 2015 Vol 15, No 3: September 2015 Vol 15, No 2: August 2015 Vol 15, No 1: July 2015 Vol 14, No 3: June 2015 Vol 14, No 2: May 2015 Vol 14, No 1: April 2015 Vol 13, No 3: March 2015 Vol 13, No 2: February 2015 Vol 13, No 1: January 2015 Vol 12, No 12: December 2014 Vol 12, No 11: November 2014 Vol 12, No 10: October 2014 Vol 12, No 9: September 2014 Vol 12, No 8: August 2014 Vol 12, No 7: July 2014 Vol 12, No 6: June 2014 Vol 12, No 5: May 2014 Vol 12, No 4: April 2014 Vol 12, No 3: March 2014 Vol 12, No 2: February 2014 Vol 12, No 1: January 2014 Vol 11, No 12: December 2013 Vol 11, No 11: November 2013 Vol 11, No 10: October 2013 Vol 11, No 9: September 2013 Vol 11, No 8: August 2013 Vol 11, No 7: July 2013 Vol 11, No 6: June 2013 Vol 11, No 5: May 2013 Vol 11, No 4: April 2013 Vol 11, No 3: March 2013 Vol 11, No 2: February 2013 Vol 11, No 1: January 2013 Vol 10, No 8: December 2012 Vol 10, No 7: November 2012 Vol 10, No 6: October 2012 Vol 10, No 5: September 2012 Vol 10, No 4: August 2012 Vol 10, No 3: July 2012 More Issue