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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 4: December 2016" : 51 Documents clear
Particle Filtering Approach for GNSS RAIM and FPGA Implementation Ershen Wang; Fuxia Yang; Gang Tong; Pingping Qu; Tao Pang
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.v14i4.4196

Abstract

The integrity monitoring system, as an integral part of aviation navigation system for global navigation satellite system (GNSS), should detect and isolated Failures or faults caused by system failures to maintain the integrity of the GNSS. The pseudorange residual noise of navigation satellites does not completely follow the Gaussian distribution, the performance of traditional filtering algorithms (such as the Kalman filtering) may be reduced due to non-Gaussian noise. The particle filter algorithm has great advantage to dealing with the nonlinear and non-Gaussian system. in this paper, the particle filter algorithm is applied to GNSS receiver autonomous integrity monitoring(RAIM) to detect the fault of navigation satellite. Firstly, Log likelihood ratio (LLR) testing is established; and then, the consistency between the state estimation of the main particle filter and the auxiliary particle filter is checked to determine whether the navigation satellite has failed; finally, the novel RAIM algorithm is undertaken by field programmable gate array (FPGA), the modules of the proposed RAIM algorithm is implemented. The effectiveness of the proposed approach is illustrated in a problem of GPS (Global Positioning System) autonomous integrity monitoring system, the algorithm and its implementation can be embeded in GNSS receiver.
SVM Parameter Optimization using Grid Search and Genetic Algorithm to Improve Classification Performance Iwan Syarif; Adam Prugel-Bennett; Gary Wills
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.v14i4.3956

Abstract

Machine Learning algorithms have been widely used to solve various kinds of data classification problems. Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicated and computationally expensive, especially when the number of possible different combinations of variables is so high. Support Vector Machine (SVM) has been proven to perform much better when dealing with high dimensional datasets and numerical features. Although SVM works well with default value, the performance of SVM can be improved significantly using parameter optimization. We applied two methods which are Grid Search and Genetic Algorithm (GA) to optimize the SVM parameters. Our experiment showed that SVM parameter optimization using grid search always finds near optimal parameter combination within the given ranges. However, grid search was very slow; therefore it was very reliable only in low dimensional datasets with few parameters. SVM parameter optimization using GA can be used to solve the problem of grid search. GA has proven to be more stable than grid search. Based on average running time on 9 datasets, GA was almost 16 times faster than grid search. Futhermore, the GA’s results were slighlty better than the grid search in 8 of 9 datasets.
Audio Spike Detection on Gamelan using Envelope Shape Pattern Analysis Solekhan Solekhan; Yoyon K Suprapto; Wirawan Wirawan
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.v14i4.4012

Abstract

Spike detection is important for the analysis of gamelan signal processing, in detecting the onset, transcription, and spikes occur on gamelan percussion instruments. Since the current methods: absolute value and NEO, could not detect spikes properly, we proposed to develop a new spike detection method. In this paper, the early stage of spike detection in gamelan music audio was the determination of the peak signal to obtain the form of a signal pattern (envelope like) which was then used as threshold for determining the spike locations. We also demonstrated the effectiveness of their method using shape pattern analysis to detect spikes.
Novel DV-hop Method Based on Krill Swarm Algorithm Used for Wireless Sensor Network Localization Yang Sun; Shoulin Yin; Jie Liu
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.v14i4.3985

Abstract

Wireless sensor network (WSN) is self-organizing network; it consists of a large number of sensor nodes with perception, calculation ability and communication ability. As we all know, the floor, walls or people moving has an effect on indoor localization, so it will result in multi-path phenomena and decrease signal strength, also the received signal strength indicator (RSSI) is unable to gain higher accuracy of positioning. When using multilateral measurement method to calculate the unknown node coordinates, it will generate big error in range-free distance vector-hop (DV-hop) localization algorithm of WSN. In order to improve the WSN positioning accuracy in indoor condition, more reasonable distribute network resources, in this paper, we firstly propose krill swarm algorithm used for WSN localization. First, we detailed analyze the multilateral measurement method in DV-hop localization algorithm. The position problem can be transformed into a global optimization problem. Then, we adequately utilize the advantage of calculating optimization problem. We apply the krill swarm algorithm into the stage of estimating unknown node coordinates in DV-hop algorithm to realize localization. Finally, the simulation experience results show that the localization with krill swarm algorithm has an obviously higher positioning precision and accuracy stability with different anchor node proportion and nodes. We also make comparison with DV-hop algorithm and the newest localization algorithm.
Planning and Coordination in Hierarchies of Intelligent Dynamic Systems Alexander Yakovlevich Fridman
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.v14i4.4997

Abstract

On the basis of the known principle of interactions prediction (Mesarovic), our earlier proposed incremental coordination principle is extended over hierarchical collectives of intelligent dynamic systems (IDSs) after Gennady Osipov. Such systems admit arbitrary types of variables in their state vector and thereby allow investigating more general dynamic systems than “classical” ones defined in numerical state spaces. Using the concept of effective N-attainability (Osipov), a straightforward procedure of planning for hierarchical collectives of IDS is developed. As soon as a plan for reaching a goal state from the current one is found, effective implementation of this plan requires for coordination of IDSs taking their parts in the collective. We consider both aspects of coordination (coordinability with respect to the coordinator’s task and coordinability in relation to the global task) and infer necessary conditions of the coordinability for a locally organized hierarchy of IDSs.
Research on Identification Method of Anonymous Fake Reviews in E-commerce Lizhen Liu; Xinlei Zhao; Hanshi Wang; Wei Song; Chao Du
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.v14i4.3654

Abstract

In this paper, a new method has been proposed for identifying anonymous fake reviews generated by click farmers in E-commerce and improves the identification rates. Anonymous fake reviews are different from the gunuine reviews. They could be distinguished based on the credibility of users, the average daily number of evaluations, the content similarity, and the degree of word overlapping. The proposed method takes into account these 5 features to calculate the fake reviews content by constructing multivariate linear regression model, Experiments show that this prelimilnary work performed well in identifying fake reviews in Chinese E-commerce website. The extracted features are also useful to identifying the fake reviews when the reviewer’s identification is not accessable.
Multi Features Content-Based Image Retrieval Using Clustering And Decision Tree Algorithm Kusrini Kusrini; M. Dedi Iskandar; Ferry Wahyu Wibowo
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.v14i4.4646

Abstract

The classification can be performed by using the decision tree approach. Previous researches on the classification using the decision tree have mostly been intended to classify text data. This paper was intended to introduce a classification application to the content-based image retrieval (CBIR) with multi-attributes by using a decision tree. The attributes used were the visual features of the image, i.e. : color moments (order 1, 2 and 3), image entropy, energy and homogeneity. K-means cluster algorithm was used to categorize each attribute. The result of categorized data was then built into a decision tree by using C4.5. To show the concept in application, this research built an application with main features, i.e.: cases data input, cases list, training process and testing process to do classification. The resulting tests of 150 rontgen data showed the training data classification’s truth value of 75.33% and testing data classification of 55.7%.
An Optimized Model for MapReduce Based on Hadoop Zhang Hong; Wang Xiao-ming; Cao Jie; Ma Yan-hong; Guo Yi-rong; Wang Min
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.v14i4.3606

Abstract

Aiming at the waste of computing resources resulting from sequential control of running mechanism of MapReduce model on Hadoop platform，Fork/Join framework has been introduced into this model to make full use of CPU resource of each node. From the perspective of fine-grained parallel data processing, combined with Fork/Join framework，a parallel and multi-thread model，this paper optimizes MapReduce model and puts forward a MapReduce+Fork/Join programming model which is a distributed and parallel architecture combined with coarse-grained and fine-grained on Hadoop platform to Support two-tier levels of parallelism architecture both in shared and distributed memory machines. A test is made under the environment of Hadoop cluster composed of four nodes. And the experimental results prove that this model really can improve performance and efficiency of the whole system and it is not only suitable for handling tasks with data intensive but also tasks with computing intensive. it is an effective optimization and improvement to the MapReduce model of big data processing.
A Practical Coordinated Trajectory Tracking for A Group of Mixed Wheeled Mobile Robots with Communication Delays Sisdarmanto Adinandra; Dwi Ana Ratnawari
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.v14i4.3056

Abstract

Coordination between a specific mobile robot type has been widely investigated, e.g coordination between unicycles. To extend the applicability of the system, a coordinated trajectory tracking of mixed type of mobile robots is considered. We prove that if a certain type of wheeled mobile robot is able to individually track its own reference, then coordination in tracking with other type of robots can be achieved simply by sharing individual tracking errors. Using two types of wheeled mobile robots, namely unicycle type (a nonholonomic mobile robot) and omni wheels type (a holonomic mobile robot), a coordinated control algorithm can achieve a global asymptotically stable condition of the error dynamics of the systems. Under bidirectional communication between robots as a constraint, the group is able to maintain individual tracking while coordinating the movements with other robots regardless occurring perturbations in the system and delays in communication channels. Simulation results suggest that information sharing between the robots increase the robustness in coordinating individual trajectories. Results also show that delays cause drop in performance similar to the case of no information sharing.
Interleaved reception method for restored vector quantization image Iman Elawady; Abdelmounaim Moulay Lakhdar; Mustapha Khelifi
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.v14i4.3181

Abstract

The transmission of image compression by vector quantization produce wrong blocks in received image which are completely different to the original one that makes the restoration process too hard because we don’t have any information about the original blocks. As a solution of this problem we try to keep the maximum of pixels that form the original block by building new blocks. Our proposition is based on decomposition and interleaving. For the simulation we use a binary symmetric channel with different BER and in the restoration process we use simple median filter just to check the efficiency of proposed approach.

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