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Journal of ICT Research and Applications
Published by Institut Teknologi Bandung
ISSN : 23375787     EISSN : 23385499     DOI : https://doi.org/10.5614/itbj.ict.res.appl.
Core Subject : Science,
Computer Science & IT
Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 6 Documents
 1 
Search results for , issue "Vol. 7 No. 3 (2013)" : 6 Documents clear
Implementation of Kadazan Tagger Based on Brill's Method Marylyn Alex; Lailatul Qadri Zakaria
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2013.7.3.1

Abstract

We present and evaluate the implementation of Part of Speech (POS) Tagging for the Kadazan language by using the Transformation-based approach. The main purpose of this study is to develop an automatic POS tagging for the Kadazan language, which had never, been developed before. POS tagging can tag the Kadazan corpus automatically and can help reduce the disambiguation problem of this language. The implementation of this approach in this study is to achieve a better and higher accuracy or at least similar to that of the other tagging approaches such as the statistical and the original rule-based approach. This approach can transform the tags based on the prescribed set of rules. A number of objectives were set in order to achieve the main purpose of this study. Firstly, to apply the lexical and contextual rules for this language. Secondly, to implement the Brill's algorithm based on the set of rules and finally to determine the effectiveness of the Kadazan Part of Speech by using this approach. The tagging system had been trained using four Kadazan corpuses containing 5663 words in all. Based on the evaluation results, the tagging system had achieved around 93% accuracy.
Characterization of Series Iteration Log-periodic Fractal Koch Printed Antenna Equipped with Balun Unit Achmad Munir; Dida Tuhu Putranto; Heroe Wijanto
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2013.7.3.2 .7.3.2

Abstract

In this paper, characterization of log-periodic fractal Koch antenna in series iteration and equipped with balance-unbalance (balun) unit is investigated numerically and experimentally. The proposed antenna which is deployed an FR-4 Epoxy dielectric substrate using printed-antenna techniques is designed based on Koch fractal geometry in series iteration to minimize its transversal dimension. Since the proposed antenna is a balanced antenna type, then it requires a balun circuit to be available being fed from a coaxial type transmission line. Prior to realization and experimental characterization, some basic antenna parameters including VSWR, impedance characteristic, gain, and radiation pattern are investigated numerically to obtain the optimum architectural design. Moreover, the number of antenna elements as well as the effect of balun unit is also analyzed numerically. From the result, it shows that the proposed antenna has a dimension of 120mm x 150mm, working bandwidth from 0.7GHz"“2.6GHz for VSWR < 2, and overall gain of more than 6dB for frequency range > 1.6GHz.
A Fast and Efficient Thinning Algorithm for Binary Images Tarik Abu-Ain; Siti Norul Huda Sheikh Abdullah; Bilal Bataineh; Khairuddin Omar
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2013.7.3.3

Abstract

Skeletonization "also known as thinning" is an important step in the pre-processing phase in many of pattern recognition techniques. The output of Skeletonization process is the skeleton of the pattern in the images. Skeletonization is a crucial process for many applications such as OCR and writer identification. However, the improvements in this area are only a recent phenomenon and still require more researches. In this paper, a new skeletonization algorithm is proposed. This algorithm combines between parallel and sequential, which is categorized under an iterative approach. The suggested method is conducted by experiments of benchmark dataset for evaluation. The outcome is to obtain much better results compared to other thinning methods that are discussed in comparison part.
Genetic Programming for Medicinal Plant Family Identification System Indra Laksmana; Yeni Herdiyeni; Ervizal A.M. Zuhud
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2013.7.3.4

Abstract

Information about medicinal plants that is available in text documents is generally quite easy to access, however, one needs some efforts to use it. This research was aimed at utilizing crucial information taken from a text document to identify the family of several species of medicinal plants using a heuristic approach, i.e. genetic programming. Each of the species has its unique features. The genetic program puts the characteristics or special features of each family into a tree form. There are a number of processes involved in the investigated method, i.e. data acquisition, booleanization, grouping of training and test data, evaluation, and analysis. The genetic program uses a training process to select the best individual, initializes a generate-rule process to create several individuals and then executes a fitness evaluation. The next procedure is a genetic operation process, which consists of tournament selection to choose the best individual based on a fitness value, the crossover operation and the mutation operation. These operations have the purpose of complementing the individual. The best individual acquired is the expected solution, which is a rule for classifying medicinal plants. This process produced three rules, one for each plant family, displaying a feature structure that distinguishes each of the families from each other. The genetic program then used these rules to identify the medicinal plants, achieving an average accuracy of 86.47%.
A Multiclass-based Classification Strategy for Rethorical Sentence Categorization from Scientific Papers Dwi H. Widyantoro; Masayu L. Khodra; Bambang Riyanto Trilaksono; E. Aminudin Aziz
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2013.7.3.5

Abstract

Rapid identification of content structures in a scientific paper is of great importance particularly for those who actively engage in frontier research. This paper presents a multi-classifier approach to identify such structures in terms of classification of rhetorical sentences in scientific papers. The idea behind this approach is based on an observation that no single classifier is the best performer for classifying all rhetorical categories of sentences. Therefore, our approach learns which classifiers are good at what categories, assign the classifiers for those categories and apply only the right classifier for classifying a given category. This paper employsk-fold cross validation over training data to obtain the category-classifier mapping and then re-learn the classification model of the corresponding classifier using full training data on that particular category. This approach has been evaluated for identifying sixteen different rhetorical categories on sentences collected from ACL-ARC paper collection. The experimental results show that the multi-classifier approach can significantly improve the classification performance over multi-label classifiers.
Cover JICTRA Vol. 7 No. 3, 2013 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 7 No. 3 (2013)
Publisher : LPPM ITB

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Abstract

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