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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 48 Documents
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Search results for , issue "Vol 14, No 2: June 2016" : 48 Documents clear
Switch Configuration Effect on Stray Capacitance in Electrical Capacitance Volume Tomography Hardware Arba’i Yusuf; Harry Sudibyo S; Dodi Sudiana; Agus Santoso Tamsir; Imamul Muttakin; Wahyu Widada; Warsito P. Taruno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3328

Abstract

Electrical capacitance volume tomography (ECVT) system uses six switches in one channel with configuration resembling “T” letter, so it is called “T-switch”. The working scheme of the switch can be explained in four different modes of operation, i.e. excitation mode, detection mode, ground mode, and floating mode. This research describes the effect of switch configuration to stray capacitance in ECVT hardware. Stray capacitance introduces parasitic signal from other sources; one of them is signal from another electrode at floating mode when the signal is still flowing to detection circuit. One channel, two channels, three channels, so on until thirty-two channels are connected to single detection circuit sequentially to investigate the effect of stray capacitance. Both simulation and experiment show the stray capacitance increases along with addition of channel corresponds to 0.046pF for each channel.
Cluster Analysis for SME Risk Analysis Documents Based on Pillar K-Means Irfan Wahyudin; Taufik Djatna; Wisnu Ananta Kusuma
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2385

Abstract

In Small Medium Enterprise’s (SME) financing risk analysis, the implementation of qualitative model by giving opinion regarding business risk is to overcome the subjectivity in quantitative model. However, there is another problem that the decision makers have difficulity to quantify the risk’s weight that delivered through those opinions. Thus, we focused on three objectives to overcome the problems that oftenly occur in qualitative model implementation. First, we modelled risk clusters using K-Means clustering, optimized by Pillar Algorithm to get the optimum number of clusters. Secondly, we performed risk measurement by calculating term-importance scores using TF-IDF combined with term-sentiment scores based on SentiWordNet 3.0 for Bahasa Indonesia. Eventually, we summarized the result by correlating the featured terms in each cluster with the 5Cs Credit Criteria. The result shows that the model is effective to group and measure the level of the risk and can be used as a basis for the decision makers in approving the loan proposal. 
State-space Modelling and Digital Controller Design for DC-DC Converter Oladimeji Ibrahim; Nor Zaihar Yahaya; Nordin Saad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3042

Abstract

The recent development in digital technology offers better platform for easy implementation of advance control algorithm in power converter design making digital control a viable alternative to analogue counterpart. Controller design for power converters has been very challenging due to non-linear characteristics of power switches, the supply voltage variability, load current changes and circuit element variation. This paper presents dynamic averaged state-space modelling of non-ideal dc-dc boost converter with parasitic and digital controller design for boost converter using digital redesign and direct digital design methods. The system was simulated in Matlab/Simulink to investigate the dynamic performance of the two controllers’ transient response, control bandwidth and response to variable supply voltage. The results demonstrated fast transient and wide control bandwidth for tight voltage regulation of variable input voltage.
Photovoltaic Array Maximum Power Point Tracking Based on Improved Method Jia Cunliang; Yanxiong Wang; Zerong Wang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2958

Abstract

At present, a good deal of methods for the Maximum Power Point Tracking (MPPT) has been used in engineering applications. However, Matlab simulation proved that they were difficult to harmonize the stability and speed ability of system. In addition, in order to maximize the use of PV panels ‘power, the paper focused on aneonatalalgorithm for Maximum Power Point Tracking (MPPT). Based on the algorithm, this paper designed an improved and feasible variable step perturbation and observation method which well alleviated the conflict that the maximum power point tracking could not take into account the stability and speed of response efficiently.
Identification of Tuna and Mackerel based on DNA Barcodes using Support Vector Machine Mulyati Mulyati; Wisnu Ananta Kusuma; Mala Nurilmala
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2469

Abstract

Tuna and mackerel are important fish in Indonesia that have great demand in the community and contain good nutrients for health. Many of the processed products have been faked including processed fish, by replacing the content of products that have high sales value to other lower price one. For ensuring food safety, fraudulent should be prevented by identifying the content of refined product. In this research, we implemented support vector machine (SVM), one of the popular methods in machine learning, to yield a model for identifying the content of refined product based on DNA barcode sequences. The feature extraction of DNA barcode Sequences was conducted by calculating k-mers frequency of each sequences. In this study, we used trinucleotide (3-mers) and tetranucleotide (4-mers). These features were inputted to SVM to classify and identify whether the DNA barcode sequences belong to the class of tuna, mackerel, or other fish. The evaluation results showed model SVM was able to perform identification with the accuracy 88%.
Application of Artificial Fish Swarm Algorithm in Radial Basis Function Neural Network Yuhong Zhou; Jiguang Duan; Limin Shao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2752

Abstract

Neural network is one of the branches with the most active research, development and application in computational intelligence and machine study. Radial basis function neural network (RBFNN) has achieved some success in more than one application field, especially in pattern recognition and functional approximation. Due to its simple structure, fast training speed and excellent generalization ability, it has been widely used. Artificial fish swarm algorithm (AFSA) is a new swarm intelligent optimization algorithm derived from the study on the preying behavior of fish swarm. This algorithm is not sensitive to the initial value and the parameter selection, but strong in robustness and simple and easy to realize and it also has parallel processing capability and global searching ability. This paper mainly researches the weight and threshold of AFSA in optimizing RBFNN. The simulation experiment proves that AFSA-RBFNN is significantly advantageous in global optimization capability and that it has outstanding global optimization ability and stability.
Semi-supervised Online Multiple Kernel Learning Algorithm for Big Data Ning Liu; Jianhua Zhao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2751

Abstract

In order to improve the performance of machine learning in big data, online multiple kernel learning algorithms are proposed in this paper. First, a supervised online multiple kernel learning algorithm for big data (SOMK_bd) is proposed to reduce the computational workload during kernel modification. In SOMK_bd, the traditional kernel learning algorithm is improved and kernel integration is only carried out in the constructed kernel subset. Next, an unsupervised online multiple kernel learning algorithm for big data (UOMK_bd) is proposed. In UOMK_bd, the traditional kernel learning algorithm is improved to adapt to the online environment and data replacement strategy is used to modify the kernel function in unsupervised manner. Then, a semi-supervised online multiple kernel learning algorithm for big data (SSOMK_bd) is proposed. Based on incremental learning, SSOMK_bd makes full use of the abundant information of large scale incomplete labeled data, and uses SOMK_bd and UOMK_bd to update the current reading data. Finally, experiments are conducted on UCI data set and the results show that the proposed algorithms are effective.
Performance Analysis of a VPV/FC Hybrid System for Generating Electricity in Iraq's Remote Areas Z. Nawawi; A.S. Aziz; Z. Buntat; M.A.B. Sidik; H.J. Kareem; M.A.A. Aziz; A.Z. Abdulameer; M.I. Jambak; Y.Z. Arief
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3749

Abstract

A reliable electrical energy supply is a prerequisite for improving the standard economic and quality of life levels in a country. As is the case in many countries, Iraq is home to a collection of remote villages. Since it is uneconomical to connect these villages to the existing grid, the installation of stand-alone electrical power generators has become common practice. As a result, diesel stand-alone power generators see widespread use in these remote locales, which, whilst fit for their intended purpose, unfortunately suffer from several drawbacks, including instability in regards to everyday oil prices and a number of environmental issues. The implementation of a PV/FC hybrid power system could be one potential alternative to help solve these problems. Therefore, this paper will present PV/FC system control strategies alongside information relating to the performance of such system components, based on a case study that was conducted in Al-Gowair, Iraq. This study is especially important in terms of envisioning the future energy supply needs of Iraq. The HOMER simulation results showed that by using the proposed control strategies and suggested components of a PV/FC system, it was able to produce a satisfactory outcome.
Critical Success Factor in Monetizing Blog Andika Rizky; Bens Pardamean
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3041

Abstract

Blog usage has transformed from its initial function as a digital diary into a legitimate form of mainstream media. Nowadays any member of the public can generate income from blogging through monetization even though various factors affect the results of this process. Four factors were identified: traffic, search engine optimization (SEO), post frequencies, and media usage. This study examines the level of importance of these factors through practical implementation into blogs then quantitatively determine which factor is critical for the success of blog monetization. An empirical analysis based on thirty samples of blogs were performed to assess the impact of the received income. The finding showed that the revenue for most of the blogs increased after the implementation of critical factors with SEO being the most critical of all the factors.
Remote Sensing Image Fusion Scheme using Directional Vector in NSCT Domain Baohui Tian; Lan Lan; Hailiang Shi; Yunxia Pei
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.2747

Abstract

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity indexA novel remote sensing image fusion scheme is presented for panchromatic and multispectral images, which is based on NonSubsampled Contourlet Transform (NSCT) and Principal Component Analysis (PCA). The fusion principles of the different subband coefficients obtained by the NSCT decomposition are discussed in detail. A PCA-based weighted average principle is presented for the lowpass subbands, and a selection principle based on the variance of the directional vector is presented for the bandpass directional subbands, in which the directional vector is assembled by the NSCT coefficients of the different directional subbands but the same coordinate. The proposed scheme is tested on two sets of remote sensing images and compared with some traditional multiscale transform-based image fusion methods, such as discrete wavelet transform, stationary wavelet transform, dual-tree complex wavelet transform, contourlet transform. Experimental results demonstrate that the proposed scheme provides superior fused image in terms of several relevant quantitative fusion evaluation indexes.

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