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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 51 Documents
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Search results for , issue "Vol 14, No 3: September 2016" : 51 Documents clear
Recognition of Fission Signals Based on Wavelet Analysis and Neural Network Li Li; Liu Keqi; Hu Gen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3544

Abstract

Because of the particularity of the uranium components, the nondestructive measuring technique is needed to detect the radioactivity of the component in certain container and identify their property to recognize all kinds of uranium components. This paper establishes a set of samples with the same shape, different weight and abundance of uranium by simulation. Secondly the cross-correlation function of time-relation signal between the source detector and the detector could be calculated. Lastly the result of cross-correlation functions is through micro-wavelet analysis to obtain feature vector which is related to the quality and abundance property of target uranium components. This vector is used to train neural network and help to identify the quality and abundance of unknown uranium components.
Critical Condition in CuInAlSe2 Growth of Solar Cell Absorber Sujarwata Sujarwata; Fianti Fianti; J.Y. Jung; S.H. Lee; K.H. Kim; M.I. Amal
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3644

Abstract

CuInAlSe2 (CIAS) thin films were prepared using pulsed laser deposition (PLD) and selenization. The PLD process utilized a certain kind of stacking order to deposit elemental films on glass substrates, layer by layer, for precursor preparation. They were designed to be Al- and Cu-deficient and selenized using two different heat treatment steps. According to its precursor compositional ratio, stacking order, and heat treatment, each CIAS film showed different properties and a critical condition. The crystalline phases, compositional ratio, morphology, and optical-electrical properties of the CIAS films are discussed here.   
A Technique to Improve Ridge Flows of Fingerprint Orientation Fields Estimation Saparudin Saparudin; Ghazali Sulong
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3112

Abstract

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity indexAn accurate estimated fingerprint orientation fields is a significant step for detection of singular points. Gradient-based methods are frequently used for estimating orientation fields but those methods are sensitive to noise. Fingerprints that perfect quality are seldom. They may be corrupted and degraded due to impression conditions or variations on skin. Enhancement of ridge flows improved the structure of orientation fields and hence increased the number of true singular points thereby conducting the overall performance of the classification process. In this paper, we provided discussion on the technique and implementation to improve local ridge flows segmentation; secondly, identification of noise areas and marking; thirdly, estimation of fingerprint orientation fields using gradient-based method and finally, enhancement of ridge flows using minimum variance of the cross centre block direction in squared gradients. A standard fingerprint database is used for testing of proposed technique to verify the tier of effectivity of algorithm. The experimental results suggest that our enhanced algorithm achieves visibly better ridge flows compare to other methods.
A Sentiment Knowledge Discovery Model in Twitter’s TV Content Using Stochastic Gradient Descent Algorithm Lira Ruhwinaningsih; Taufik Djatna
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.2671

Abstract

The use of social media that the explosive can be a rich source for data mining. Meanwhile, the development of television programs become increased and varied so motivate people to make comments on it’s via social media. Social network contains abundant information which is unstructured, heterogeneous, high dimensional and incremental in nature. Abundant data can be a rich source of information but it is difficult to identify manually. The contributions of this research are to perform preprocessing to address unstructured data, a lot of noise and heterogeneous; find patterns of information and knowledge of social media user activities in the form of positive and negative sentiment on twitter TV content. Some methodologies and techniques are used to perform preprocessing. They are eliminates punctuation and symbols, eliminates number, replace numbers into letters, translation of Alay words, eliminate stop word and Stemming Porter Algorithm. Methodology of this study was used Stochastic Gradient Descent (SGD).The text that has been through preprocessing produces a more structured text, reducing noise and reducing the diversity of text. So, preprocessing affect to the correctly classified istances and processing time. The experiment results reveal that the use of SGD for discovery of the positive and negative sentiment tends to be faster for large data or stream data. Correctly classified instance with a maximum of 88%.
Ventricular Tachyarrhythmia Prediction based on Heart Rate Variability and Genetic Algorithm Khang Hua Boon; Malarvili Bala Krishnan; Mohamed Khalil-Hani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3665

Abstract

Predicting ventricular tachyarrhythmia (VTA) provides opportunities to reduce casualties due to sudden cardiac death. However, prediction accuracy is still need improvement. In this paper, we propose a method that can predict VTA events using support vector machine (SVM) that trained with HRV features from heart rate variability (HRV). The Spontaneous Ventricular Tachyarrhythmia Database (Medtronic Version 1.0), comprising 106 pre-VT records, 26 pre-VF records, and 135 control data, is used.  Fifty percent of the data was used to train the SVM, and the remainder was used to verify the performance. Each data set was subjected to preprocessing and HRV feature extraction. After correcting the ectopic beats, 5 minutes RR intervals prior to each event was cropped for feature extraction. Extraction of the time domain, spectral, non-linear and bispectrum features were performed subsequently. Furthermore, both t-test and genetic algorithm (GA) were used to optimize the HRV feature subset. With optimized feature subset by GA, proposed method of current work able to outperform previous works with 77.94%, 80.88% and 79.41 % for senstivity, specificity and accuracy respectively.
An Improved Adaptive Niche Differential Evolution Algorithm Hui Wang; Changtong Song
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3591

Abstract

Differential evolution (DE) algorithm is a random search algorithm by referring to the natural genetic and natural selection mechanism of the biological world and it is used to process the complicated non-linear problems which are difficult to be solved by traditional computational methods. However, subject to its own mechanism and single structure, the basic DE algorithm is easy to get trapped into local optimum and it is difficult to handle high-dimensional and complicated optimization problems. In order to enhance the search performance of the DE algorithm, this paper uses the idea of niche, decomposes the entire population into several niches according to the fitness, perform population selection by integrating the optimum reservation strategy to realize the optimal selection of niche, adjusts the fitness of the individual of the population, designs the adaptive crossover and mutation operators to make the crossover and mutation probabilities change with the individual fitness and enhances the ability of DE algorithm to jump out of the local optimal solution. The experiment result of benchmark function shows that the method of this paper can maintain solution diversity, effectively avoid premature convergence and enhance the global search ability of DE algorithm.
MRI Sagittal Image Segmentation from Patients with Abdominal Aortic Aneurysms Desti Riminarsih; Cut Maisyarah Karyati; Achmad Benny Mutiara; Bambang Wahyudi; E. Ernastuti
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3520

Abstract

Early detection in patients with abdominal aortic aneurysm (AAA) is esdential to reduce the risk of rupture of aortic wall that causes bleeding and often lead to death. Information about the condition of AAA is indispendable to complete the diagnosis of doctors in decision making. The position and shape of AAA can be obtained by sagittal image from an MRI examination. Characteristics of MRI sagittal image are having a gray level that is almost teh same between one organ to another. Therefore, to separate between one organ to another is difficult. This research is conducted MRI sagittal iamge segmentation in patients to obtain information on morphology and location of abdominal aortic aneurysm (AAA). To Segmenting the MRI Image we comobine thresholding method and Haralick Method. Under this proposed method, obtained sagittal images of the aorta are used to gain information about the location and shape of the aneurysm in abdominal aorta.
Nurses Scheduling by Considering the Qualification using Integer Linear Programming Maya Widyastiti; Amril Aman; Toni Bakhtiar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.2913

Abstract

One of problems that frequently occurs in hospital management is nurses scheduling problem. A suitable schedule is needed in order to avoid fatigue, both physically and psychologically, which subsequently may deteriorate their performance. Nurse scheduling is commonly designed by the head of nurse manually. In this research, nurse scheduling problem is modeled by considering the qualification of the nurses and the model has the form of integer linear programming. The objective of the model is to maximize the number of nurse’s day-offs. Then optimization problem is implemented to nurses scheduling in the High Care Unit and the Emergency room of Rumah Sehat Terpadu Dompet Dhuafa Parung Bogor.
Sensitivity Analysis and Comparison between 25 kW Parabolic Dish System Mohd Ruddin Ab Ghani; Liaw Geok Pheng; Chin Kim Gan; Tole Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.4056

Abstract

Dish-Stirling concentrating solar power systems is an efficient and reliable source of renewable energy. In this paper, the proposed model showed the idea of Parabolic Dish (PD) systems with control system model which vary the amount of working gas in the Stirling engine. The control systems were designed using Matlab /Simulink 2012a. Based on the developed linearized model, an improved temperature controller with transient droop characteristic and Mean Pressure Control (MPC) has been proposed. This temperature controller was effective in reducing the temperature and improving performance of the PD system. The overall performance of the system improved more than 78% in output power and energy. Besides, the system improved in term of sensitivity compared with the PD system without compensated. In addition, thermal losses decreased to 97.6% which is directly have significant improvement for the output efficiency to the system. The analysis shows that the PD system is feasible in term of technical but not economically feasible in the Malaysia environment.
A New Semi-supervised Clustering Algorithm Based on Variational Bayesian and Its Application Shoulin Yin; Jie Liu; Lin Teng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3805

Abstract

Biclustering algorithm is proposed for discovering matrix with biological significance in gene expression data matrix and it is used widely in machine learning which can cluster the row and column of matrix. In order to further improve the performance of biclustering algorithm, this paper proposes a semi-supervised clustering algorithm based on variational Bayesian. Firstly, it introduces supplementary information of row and column for biclustering process and represents corresponding joint distribution probability model. In addition, it estimates the parameter of joint distribution probability model based on variational Bayesian learning method. Finally, it estimates the performance of proposed algorithm through synthesized data and real gene expression data set. Experiments show that normalized mutual information of this paper’s new method is better than relevant biclustering algorithms for biclustering analysis.

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