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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 29 Documents
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Search results for , issue "Vol 11, No 3: September 2013" : 29 Documents clear
Comparative Study of Bankruptcy Prediction Models Isye Arieshanti; Yudhi Purwananto; Ariestia Ramadhani; Mohamat Ulin Nuha; Nurissaidah Ulinnuha
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1143

Abstract

 Early indication of Bankruptcy is important for a company. If companies aware of potency of their Bankruptcy, they can take a preventive action to anticipate the Bankruptcy. In order to detect the potency of a Bankruptcy, a company can utilize a model of Bankruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for Bankruptcy prediction. It is expected that the comparison result will provide insight about the robust method for further research. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP), Hybrid of MLP + Multiple Linear Regression), it can be concluded that fuzzy k-NN method achieve the best performance with accuracy 77.5%. The result suggests that the enhanced development of bankruptcy prediction model could use the improvement or modification of fuzzy k-NN.
Research and Design in Unified Coding Architecture for Smart Grids Gang Han; Jianwen Zhang; Xin Chu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.951

Abstract

 Standardized and sharing information platform is the foundation of the Smart Grids. In order to improve the dispatching center information integration of the power grids and achieve efficient data exchange, sharing and interoperability, a unified coding architecture is proposed. The architecture includes coding management layer, coding generation layer, information models layer and application system layer. Hierarchical design makes the whole coding architecture to adapt to different application environments, different interfaces, loosely coupled requirements, which can realize the integration model management function of the power grids. The life cycle and evaluation method of survival of unified coding architecture is proposed. It can ensure the stability and availability of the coding architecture. Finally, the development direction of coding technology of the Smart Grids in future is prospected.
Adaptive Control for Robotic Manipulators base on RBF Neural Network Ma Jing Ma Jing; Zhang Wenhui; Zhu Haiping
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1131

Abstract

An adaptive neural network controller is brought forward by the paper to solve trajectory tracking problems of robotic manipulators with uncertainties.  The  first  scheme consists of  a PD feedback  and  a  dynamic  compensator  which is  composed by  neural  network controller and  variable  structure controller.  Neutral network controller is designed to adaptive learn and compensate the unknown uncertainties, variable   structure controller is designed to eliminate approach errors of neutral network. The adaptive weight learning algorithm of neural network is designed to ensure online real-time adjustment, offline learning phase is not need; Global asymptotic stability (GAS) of system base on Lyapunov theory is analysised to ensure the convergence of the algorithm. The simulation results show that the kind of the control scheme is effective and has good robustness.
Adaptive Control for Robotic Manipulators base on RBF Neural Network Ma Jing Ma Jing; Zhang Wenhui; Zhu Haiping
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.986

Abstract

An adaptive neural network controller is brought forward by the paper to solve trajectory tracking problems of robotic manipulators with uncertainties.  The  first  scheme consists of  a PD feedback  and  a  dynamic  compensator  which is  composed by  neural  network controller and  variable  structure controller.  Neutral network controller is designed to adaptive learn and compensate the unknown uncertainties, variable   structure controller is designed to eliminate approach errors of neutral network. The adaptive weight learning algorithm of neural network is designed to ensure online real-time adjustment, offline learning phase is not need; Global asymptotic stability (GAS) of system base on Lyapunov theory is analysised to ensure the convergence of the algorithm. The simulation results show that the kind of the control scheme is effective and has good robustness.
The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm Yandra Arkeman; Akhmad Yusuf; Mushthofa Mushthofa; Gibtha FitriLaxmi; Kudang Boro Seminar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1148

Abstract

 Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II) technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.
Numerical Calculation of Transient Thermal Characteristics in Gas-Insulated Transmission Lines Li Hongtao Li Hongtao; Shu Naiqiu; Li Ling Li Ling; Wu Xiaowen Wu Xiaowen
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.945

Abstract

For further knowledge of the thermal characteristics in gas-insulated transmission lines (GILs) installed above ground, a finite-element model of coupling fluid field and thermal field is established, in which the corresponding assumptions and boundary conditions are given.  Transient temperature rise processes of the GIL under the conditions of variable ambient temperature, wind velocity and solar radiation are respectively investigated. Equivalent of surface convective heat transfer coefficient and heat flux boundary conditions are updated in the analysis process. Unlike the traditional finite element method (FEM), the variability of the thermal properties with temperature is considered. The calculation results are validated by the tests results reported in the literature. The conclusion provides method and theory basis for the knowledge of transient temperature rise characteristics of GILs in open environment.
Reconstruction of Planar Multilayered Structures using Multiplicative-Regularized Contrast Source Inversion Mudrik Alaydrus; Said Attamimi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1138

Abstract

 There is an increasing interest to have an access to hidden objects without making any destructive action. Such non-destructive method is able to give a picture of the inner part of the structure by measuring some external entities. The problem of reconstructing planar multilayered structures based on given scattering data is an inverse problem. Inverse problems are ill-posed, beside matrix inversion tools, a regularization procedure must be applied additionally. Multiplicative regularization was considered as an appropriate penalty method to solve this problem. The Gauss-Newton inversion method as an optimization procedure was used to find the permittivity values, which minimized some cost functions. Several dielectric layers with different thickness and profiles were observed. Some layers needed more discretization elements and more iteration steps to give the correct profiles. 
H-Bridge based Five-Level Current-Source Inverter for Grid Connected Photovoltaic Power Conditioner Suroso Suroso; Daru Tri Nugroho; Toshihiko Noguchi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.979

Abstract

         This paper presents an application of a new circuit configuration of H-bridge based five-level current-source inverter (CSI) used for grid connected photovoltaics system. In this topology, the intermediate level currents of the five-level current waveform are generated by connecting DC current module to the H-bridge CSI. Some new features can be derived using this new topology such as reducing the switching power device count, and reducing the inductor conduction losses of the inverter. The proposed five-level CSI is tested for grid connected photovoltaic system through computer simulation using PSIM software. Furthermore, the experimental test results of the proposed five-level CSI are presented. The results show that the inverter works properly generating a five-level current waveform and injecting a sinusoidal current into power grid with less harmonics distortion and with unity power factor operation.
Development of Blumlein Line Generator and Reactor for Wastewater Treatment Zainuddin Nawawi; Muhammad Abu Bakar Sidik; Zolkafle Buntat; S. M. Zafar Iqbal; Hashem Ahmadi; Muhammadjavad Mobarra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.952

Abstract

There are several wastewater treatment methods and techniques which have been introduced such as by using biological, chemical, and physical process. However, it is found that there are some shortcomings in the current available methods and techniques. For instance, the application of chlorine can cause bacterial disinfection but produce secondary harmful carcinogenic disinfection. In order to acquire a better understanding in wastewater treatment process, a study of wastewater treatment system and hybrid discharge reactor to acquire gas liquid phase corona like discharge is carried out. In addition to the laboratory experiment, designing and development of the Blumlein pulse power circuit and modification of reactor for wastewater treatment are accomplished as well. The Blumlein pulse power circuit generates nanosecond high voltage pulses. The Hybrid Discharge reactor can produce both spark discharge in gas phase and liquid phase (spark-spark discharge). Analysis of the emission spectrum of the occurring discharge found the existence of various chemicals such as OH radicals. In addition, a drastic improvement in terms of oxygen content and conductivity level of the wastewater sample is also observed. 
Wide Baseline Matching Using Support Vector Regression Haifeng Xi Haifeng Xi; Weihua Cui
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i3.1144

Abstract

  In this paper, we newly solve wide baseline matching using support vector regression (SVR). High correct ratio initial matches are used to train SVR relationships, obtained by matching large-scale SIFT features and discarding some mismatches by our improved topological filtering scheme; and new matches are searched near the prediction given by trained SVR relationships. Both indoor and outdoor environments image pairs under wide baseline condition are tested, experiment results show that our algorithm automatically gain large numbers of accurate point correspondences.

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