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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 2,614 Documents
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Parallel classification and optimization of telco trouble ticket dataset Fauzy Bin Che Yayah; Khairil Imran Ghauth; Choo-Yee Ting
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 3: June 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i3.18159

Abstract

In the big data age, extracting applicable information using traditional machine learning methodology is very challenging. This problem emerges from the restricted design of existing traditional machine learning algorithms, which do not entirely support large datasets and distributed processing. The large volume of data nowadays demands an efficient method of building machine-learning classifiers to classify big data. New research is proposed to solve problems by converting traditional machine learning classification into a parallel capable. Apache Spark is recommended as the primary data processing framework for the research activities. The dataset used in this research is related to the telco trouble ticket, identified as one of the large volume datasets. The study aims to solve the data classification problem in a single machine using traditional classifiers such as W-J48. The proposed solution is to enable a conventional classifier to execute the classification method using big data platforms such as Hadoop. This study’s significant contribution is the output matrix evaluation, such as accuracy and computational time taken from both ways resulting from hyper-parameter tuning and improvement of W-J48 classification accuracy for the telco trouble ticket dataset. Additional optimization and estimation techniques have been incorporated into the study, such as grid search and cross-validation method, which significantly improves classification accuracy by 22.62% and reduces the classification time by 21.1% in parallel execution inside the big data environment.
An Image Compression Method Based on Wavelet Transform and Neural Network Suqing Zhang; Aiqiang Wang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.1430

Abstract

Image compression is to compress the redundancy between the pixels as much as possible by using the correlation between the neighborhood pixels so as to reduce the transmission bandwidth and the storage space. This paper applies the integration of wavelet analysis and artificial neural network in the image compression, discusses its performance in the image compression theoretically, analyzes the multi-resolution analysis thought, constructs a wavelet neural network model which is used in the improved image compression and gives the corresponding algorithm. Only the weight in the output layer of the wavelet neural network needs training while the weight of the input layer can be determined according to the relationship between the interval of the sampling points and the interval of the compactly-supported intervals. Once determined, training is unnecessary, in this way, it accelerates the training speed of the wavelet neural network and solves the problem that it is difficult to determine the nodes of the hidden layer in the traditional neural network. The computer simulation experiment shows that the algorithm of this paper has more excellent compression effect than the traditional neural network method.
Modeling of Maximum Power Point Tracking Controller for Solar Power System Aryuanto Soetedjo; Abraham Lomi; Yusuf Ismail Nakhoda; Awan Uji Krismanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 10, No 3: September 2012
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v10i3.819

Abstract

 In this paper, a Maximum Power Point Tracking (MPPT) controller for solar power system is modeled using MATLAB Simulink. The model consists of PV module, buck converter, and MPPT controller. The contribution of the work is in the modeling of buck converter using equation model approach rather than circuit model one.  The buck converter model is developed using equation model that allowing the input voltage of the converter, i.e. output voltage of PV is changed by varying the duty cycle, so that the maximum power point could be tracked when the environmental changes. From the experiment, the developed model comforms with the circuit model provided by MATLAB Simulink Power Simulation. Furher, the simulation results show that the developed model performs well in tracking the maximum power point (MPP) of the PV module using Perturb and Observe (P&O) Algorithm. 
Feature Selection Method Based on Improved Document Frequency Wei Zheng; Guohe Feng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i4.536

Abstract

Feature selection is an important part of the process of text classification, there is a direct impact on the quality of feature selection because of the evaluation function. Document frequency (DF) is one of several commonly methods used feature selection, its shortcomings is the lack of theoretical basis on function construction, it will tend to select high-frequency words in selecting. To solve the problem, we put forward a improved algorithm named DFM combined with class distribution of characteristics and realize the algorithm with programming, DFM were compared with some feature selection method commonly used with experimental using support vector machine, as text classification .The results show that, when feature selection, the DFM methods performance is stable at work and is better than other methods in classification results.
Adaptive Fuzzy Sliding Mode Control for a Class of Nonlinear System Xue Xiao; Zheng Zheng; Dong Haobin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 4: December 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i4.1898

Abstract

For a class of nonlinear system with parameter perturbation and external disturbance, adaptive fuzzy control can be used to approach the system unknown functions to reduce the control input and the steady-state error. And an adaptive switch control gain whose adaptive law is decreasing function is designed to weaken the system chattering, the switch gain of estimate will increase on the basis of the original without decreasing with the elimination of interference. If system is interferenced many times. Against the shortcomings, this paper proposes an improved adaptive law that can weaken the system chattering effectively while maintaining the strong robustness. The simulation results by tests show that this method is correct and effective.
Region Based Image Retrieval Using Ratio of Proportional Overlapping Object Agus Zainal Arifin; Rizka Wakhidatus Sholikah; Dimas Fanny H. P.; Dini Adni Navastara
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 4: December 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i4.4289

Abstract

In Region Based Image Retrieval (RBIR), determination of the relevant block in query region is based on the percentage of image objects that overlap with each sub-blocks. But in some images, the size of relevant objects are small. It may cause the object to be ignored in determining the relevant sub-blocks. Therefore, in this study we proposed a system of RBIR based on the percentage of proportional objects that overlap with sub-blocks. Each sub-blocks is selected as a query region. The color and texture features of the query region will be extracted by using HSV histogram and Local Binary Pattern (LBP), respectively. We also used shape as global feature by applying invariant moment as descriptor. Experimental results show that the proposed method has average precision with 74%.
Embedded Applications of MS-PSO-BP on Wind/Storage Power Forecasting Jianhong Zhu; Wen-xia Pan; Zhi-ping Zhang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.6720

Abstract

Higher proportion wind power penetration has great impact on grid operation and dispatching, intelligent hybrid algorithm is proposed to cope with inaccurate schedule forecast. Firstly, hybrid algorithm of MS-PSO-BP (Mathematical Statistics, Particle Swarm Optimization, Back Propagation neural network) is proposed to improve the wind power system prediction accuracy. MS is used to optimize artificial neural network training sample, PSO-BP (particle swarm combined with back propagation neural network) is employed on prediction error dynamic revision. From the angle of root mean square error (RMSE), the mean absolute error (MAE) and convergence rate, analysis and comparison of several intelligent algorithms (BP, RBP, PSO-BP, MS-BP, MS-RBP, MS-PSO-BP) are done to verify the availability of the proposed prediction method. Further, due to the physical function of energy storage in improving accuracy of schedule pre-fabrication, a mathematical statistical method is proposed to determine the optimal capacity of the storage batteries in power forecasting based on the historical statistical data of wind farm. Algorithm feasibility is validated by application of experiment simulation and comparative analysis.
Optimum Work Frequency for Marine Monitoring Based on Genetic Algorithm Fahraini Bacharuddin; Hadi Wuryanto; Yuliza Yuliza; Beny Nugraha
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7328

Abstract

The communication using of HF (High Frequency) is a system that depends on wave propagation using sky waves reflected by the earth's ionosphere layer so that it is highly effective for long distance communication, but highly dependent on varying ionospheric conditions from day and night (time after time) as well as the location of the transmitter and receiver radio. Currently, there is only one main frequency channel and one reserve frequency channel so that there are frequency constraints unable to communicate due to ionosphere changes. This research will predicted allocation of HF frequency to support long distance communication for marine monitoring using Genetic Algorithm method. Output or prediction results in the form of Optimum Work Frequency (OWF) for 24 hours and frequency graph.
Squirrel cage induction motor scalar control constant V/F analysis K. A. M. Annuar; M. R. Sapiee; Rozilawati M. Nor; M. S. M. Azali; M. B. N. Shah; Sahazati Md. Rozali
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 1: February 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i1.8818

Abstract

In constant V/f control technique it is assume that the stator resistance and leakage inductance drops are negligible, especially at high speed and small load. In other words, the back emf is comparatively large at high speed and hence these voltage drops can be neglected. By maintaining constant V/f, constant Eg/f and hence constant air-gap flux is assumed. This assumption is however invalid at low speeds since a significant voltage drop appears across the stator impedance. The terminal voltage, V no longer approximates  ag. By using MATLAB Simulink, the open-loop constant V/f is simulated. It is shown that the performance of the drive deteriorates at low speeds. The improvement in the performance by applying voltage boost is shown and discussed.
Energy-efficient MAC protocols for wireless sensor networks: a survey Abdelmalek Djimli; Salah Merniz; Saad Harous
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.12163

Abstract

MAC Protocols enables sensor nodes of the same WSN to access a common shared communication channel. Many researchers have proposed different solutions explaining how to design and implement these protocols. The main goal of most MACs protocols is how to prolong lifetime of the WSN as long as possible by reducing energy consumption since it is often impossible to change or to recharge sensors’ batteries. The majority of these protocols designed for WSN are based on “duty-cycle” technique. Every node of the WSN operates on two periods: active period and sleep period to save energy. Until now (to our knowledge) there is no ideal protocol for this purpose. The main reason relies on the lack of standardization at lower layers (physical layer) and (physical) sensor hardware.  Therefore, the MAC protocol choice remains application-dependent. A useful MAC protocol should be able to adapt to network changes (topology, nodes density and network size). This paper surveys MAC protocols for WSNs and discusses the main characteristics, advantages and disadvantages of currently popular protocols.

Page 30 of 262 | Total Record : 2614

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