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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 40 Documents
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Search results for , issue "Vol 19, No 1: February 2021" : 40 Documents clear
A hybrid naïve Bayes based on similarity measure to optimize the mixed-data classification Fatima El Barakaz; Omar Boutkhoum; Abdelmajid El Moutaouakkil
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.18024

Abstract

In this paper, a hybrid method has been introduced to improve the classification performance of naïve Bayes (NB) for the mixed dataset and multi-class problems. This proposed method relies on a similarity measure which is applied to portions that are not correctly classified by NB. Since the data contains a multi-valued short text with rare words that limit the NB performance, we have employed an adapted selective classifier based on similarities (CSBS) classifier to exceed the NB limitations and included the rare words in the computation. This action has been achieved by transforming the formula from the product of the probabilities of the categorical variable to its sum weighted by numerical variable. The proposed algorithm has been experimented on card payment transaction data that contains the label of transactions: the multi-valued short text and the transaction amount. Based on K-fold cross validation, the evaluation results confirm that the proposed method achieved better results in terms of precision, recall, and F-score compared to NB and CSBS classifiers separately. Besides, the fact of converting a product form to a sum gives more chance to rare words to optimize the text classification, which is another advantage of the proposed method.
Quantitative estimation of TV white space in Southwest Nigeria Ilesanmi Banjo Oluwafemi; Ayodeji Peter Bamisaye; Matthew Adedeji Faluru
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.17881

Abstract

The demand for bandwidth has increased in recent years with the advent of new technologies in the wireless systems which have resulted into spectrum crunch. Utilizing the free ultra high frequency (UHF), television (TV) channels also known as TV white space (TVWS) has been proposed as a strategy for increasing spectral efficiency. Deploying TVWS requires the knowledge of the estimate of the available TVWS. In this paper, a quantitative estimation of the available TVWS in South West, Nigeria is computed using the protection view point approach, the pollution viewpoint approach and the Federal Communication Commission (FCC) rule. Results from the estimation shows that the pollution view point approach will guarantee enough protection from the primary users and hence prevent interference from the secondary users. The findings also reveal that there are abundant TVWS in the considered states for the deployment of TVWS devices.
Measuring memetic algorithm performance on image fingerprints dataset Priati Assiroj; H. L. H. S. Warnars; E. Abdurrachman; A. I. Kistijantoro; A. Doucet
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16418

Abstract

Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is matching input fingerprint with data that saved in the database. In this paper, we measure the performance of the memetic algorithm to process the image fingerprints dataset. Before we run this algorithm, we divide our fingerprints into four groups according to its characteristics and make 15 specimens of data, do four partial tests and at the last of work we measure all computation time.
WEIDJ: Development of a new algorithm for semi-structured web data extraction Ily Amalina Ahmad Sabri; Mustafa Man
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16205

Abstract

In the era of industrial digitalization, people are increasingly investing in solutions that allow their process for data collection, data analysis and performance improvement. In this paper, advancing web scale knowledge extraction and alignment by integrating few sources by exploring different methods of aggregation and attention is considered in order focusing on image information. The main aim of data extraction with regards to semi-structured data is to retrieve beneficial information from the web. The data from web also known as deep web is retrievable but it requires request through form submission because it cannot be performed by any search engines. As the HTML documents start to grow larger, it has been found that the process of data extraction has been plagued with lengthy processing time. In this research work, we propose an improved model namely wrapper extraction of image using document object model (DOM) and JavaScript object notation data (JSON) (WEIDJ) in response to the promising results of mining in a higher volume of image from a various type of format. To observe the efficiency of WEIDJ, we compare the performance of data extraction by different level of page extraction with VIBS, MDR, DEPTA and VIDE. It has yielded the best results in Precision with 100, Recall with 97.93103 and F-measure with 98.9547.
Extractive multi document summarization using harmony search algorithm Zuhair Hussein Ali; Ahmed Kawther Hussein; Haithem Kareem Abass; Elham Fadel
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15766

Abstract

The exponential growth of information on the internet makes it troublesome for users to get valuable information. Text summarization is the process to overcome such a problem. An adequate summary must have wide coverage, high diversity, and high readability. In this article, a new method for multi-document summarization has been supposed based on a harmony search algorithm that optimizes the coverage, diversity, and readability. Concerning the benchmark dataset Text Analysis Conference (TAC-2011), the ROUGE package used to measure the effectiveness of the proposed model. The calculated results support the effectiveness of the proposed approach.
Predicting the notch band frequency of an ultra-wideband antenna using artificial neural networks Lahcen Aguni; Samira Chabaa; Saida Ibnyaich; Abdelouhab Zeroual
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15912

Abstract

In this paper we propose to predict the notch frequency of an ultra-wideband (UWB) antenna which operates in the frequency band from 3.85 GHz to 12.38 GHz. The prediction of the notch frequency in order to avoid interferences between (WLAN) IEEE802.11a and HIPERLAN/2 WLAN applications and UWB technology is achieved using the artificial neural networks (ANN) technique. The developed ANN is optimized with the help of K-fold cross validation method which allows us to divide the datasets into 10 subsets in the training phase. The simulated datasets are generated by controlling high frequency structural simulator (HFSS) from MATLAB using a VB script. The performance of the ANN technique is assessed using some statistical criteria. During the training process, the mean absolute percentage error (MAPE) between the simulated and the predicted ANN notch frequencies is 0,125. A comparison between simulated, theoretical, and ANN results has been achieved during the test and validation process, good accuracy is obtained between the simulated and the ANN predictions. The proposed UWB antenna exhibits a notch band from 5.1 GHz to 6.0 GHz with a notch frequency of approximately 5.51 GHz.
Comparison of data recovery techniques on master file table between Aho-Corasick and logical data recovery based on efficiency Hussein Ismael Sahib; Nurul Hidayah Ab Rahman; Ali Kazem Al-Qaysi; Mothana L. Attiah
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16276

Abstract

Data recovery is one of the tools used to obtain digital forensics from various storage media that rely entirely on the file system used to organize files in these media. In this paper, two of the latest techniques of file recovery from file system (new technology file system (NTFS)) logical data recovery, Aho-Corasick data recovery were studied, examined and a practical comparison was made between these two techniques according to the speed and accuracy factors using three global datasets. It was noted that all previous studies in this field completely ignored the time criterion despite the importance of this standard. On the other hand, algorithms developed with other algorithms were not compared. The proposed comparison of this paper aims to detect the weaknesses and strength of both algorithms to develop a new algorithm that is more accurate and faster than both algorithms. The paper concluded that the logical algorithm was superior to the Aho-Corasick algorithm according to the speed criterion, whereas the algorithms gave the same results according to the accuracy criterion. The paper leads to a set of suggestions for future research aimed at achieving a highly efficient and high-speed data recovery algorithm such as the file-carving algorithm.
Embedded processor system for controllable period-width multichannel pulse width modulation signals Mazin Rejab Khalil; Laith A. Mohammeed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16432

Abstract

This paper proposes a sophisticated embedded processor system configured on zynq-xc7z020 field programmable gate array (FPGA) device for generating four channels pulse width modulation signals with variable duty cycles and periods using embedded design techniques. The main advantages of the technique are the high ability to perform a simultaneous control on period and pulse width of the generated signals and a high system design adaptation to choose the number of input/output channels. Controlling the the period and the pulse width is achieved by injecting a digital signal to the designed system to manipulate embedded timers’ operation. Vivado design suite is used to develop the system hard ware in the integrated development environment where the processing unit and peripherals are instantiated and interconnected. A practical aplication program in C language is prepared to make the system act according to the target. The designed system can be used to drive multi-phase D.C to D.C convertors. The system performance is verified by using vivado logic analyzer and chipscope windows. The superiority of the proposed approach over other approaches is that it resulted in a multi-inputs/multi-outputs pulse width modulation system with high controllability on the pulse width and the period that ranges from 15 nsec to 60 sec.
Smartphone indoor positioning based on enhanced BLE beacon multi-lateration Ngoc-Son Duong; Thai-Mai Dinh Thi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.16275

Abstract

In this paper, we introduce a smartphone indoor positioning method using bluetooth low energy (BLE) beacon multilateration. At first, based on signal strength analysis, we construct a distance calculation model for BLE beacons. Then, with the aims to improve positioning accuracy, we propose an improved lateral method (range-based method) which is applied for 4 nearby beacons. The method is intended to design a real-time system for some services such as emergency assistance, personal localization and tracking, location-based advertising and marketing, etc. Experimental results show that the proposed method achieves high accuracy when compared with the state of the art lateral methods such as geometry-based (conventional trilateration), least square estimation-based (LSE-based) and weighted LSE-based.
Fine-grained or coarse-grained? Strategies for implementing parallel genetic algorithms in a programmable neuromorphic platform Indar Sugiarto; Steve Furber
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.15026

Abstract

Genetic Algorithm (GA) is one of popular heuristic-based optimization methods that attracts engineers and scientists for many years. With the advancement of multi- and many-core technologies, GAs are transformed into more powerful tools by parallelising their core processes. This paper describes a feasibility study of implementing parallel GAs (pGAs) on a SpiNNaker. As a many-core neuromorphic platform, SpiNNaker offers a possibility to scale-up a parallelised algorithm, such as a pGA, whilst offering low power consumption on its processing and communication overhead. However, due to its small packets distribution mechanism and constrained processing resources, parallelising processes of a GA in SpiNNaker is challenging. In this paper we show how a pGA can be implemented on SpiNNaker and analyse its performance. Due to inherently numerous parameter and classification of pGAs, we evaluate only the most common aspects of a pGA and use some artificial benchmarking test functions. The experiments produced some promising results that may lead to further developments of massively parallel GAs on SpiNNaker.

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