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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 7 Documents
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Search results for , issue "Vol. 12 No. 2 (2018)" : 7 Documents clear
Optimization of Spaced K-mer Frequency Feature Extraction using Genetic Algorithms for Metagenome Fragment Classification Arini Pekuwali; Wisnu Ananta Kusuma; Agus Buono
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.2

Abstract

K-mer frequencies are commonly used in extracting features from metagenome fragments. In spite of this, researchers have found that their use is still inefficient. In this research, a genetic algorithm was employed to find optimally spaced k-mers. These were obtained by generating the possible combinations of match positions and don't care positions (written as *). This approach was adopted from the concept of spaced seeds in PatternHunter. The use of spaced k-mers could reduce the size of the k-mer frequency feature's dimension. To measure the accuracy of the proposed method we used the naïve Bayesian classifier (NBC). The result showed that the chromosome 111111110001, representing spaced k-mer model [111 1111 10001], was the best chromosome, with a higher fitness (85.42) than that of the k-mer frequency feature. Moreover, the proposed approach also reduced the feature extraction time. 
An Analysis of Graph Properties for Detecting Sybil Nodes in Social Networks Korkiat Kaewking; Sirapat Boonkrong
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.6

Abstract

This research concerns the analysis of social networks using graph theory to find properties that can be used to determine Sybil nodes. This research also investigated the mixing time, which is one of the properties that many existing methods use for detecting Sybil attacks. The results showed that the mixing time does not reflect the difference between honest graphs and Sybil graphs. In addition, the properties of social graphs were studied and it was found that the average node distance is different in graphs containing Sybil nodes than in graphs with only honest nodes. Furthermore, the eigenvector centrality and the degree of Sybil nodes are correlated, while in honest nodes they are not.
Which Tech Will I Use? Trends in Students’ Use and Ownership of Technology in a Thai University, an Ongoing Study Yuwanuch Gulateee; Jeremy Pagram; Babara Combes
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.3

Abstract

Students’ ownership of technology devices, their access to software and Web-based utilities, and their related preferences are the subject of this ongoing research. The devices that instructors use in the classroom, how students use online learning systems as provided by the university, and students’ skill levels when using technology for learning are also included. The major objective of this research is to provide a long-term comparative analysis across one university to determine if students’ and lecturers’ use of technology for teaching-learning has changed. Such ongoing data collection and analysis will inform individual institutions about online learning and how to improve facilities for both staff and students for maximum educational success. An initial study was conducted in 2015. This paper reports on the second data collection to determine if there have been any changes over a two-year period. The findings indicate that students have intermediate skill levels when using basic software programs for their study, whereas their social media skills are advanced. Students use mobile devices (phones and tablets) to access online learning materials. Overall, most students and staff lack basic knowledge in using information technology for study purposes. It was concluded that the university should continue to conduct ongoing monitoring and evaluation of students’ and staff’s information technology competencies.
Safe Driving using Vision-based Hand Gesture Recognition System in Non-uniform Illumination Conditions Shalini Anant; Shanmugham Veni
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.4

Abstract

Nowadays, there is tremendous growth in in-car interfaces for driver safety and comfort, but controlling these devices while driving requires the driver's attention. One of the solutions to reduce the number of glances at these interfaces is to design an advanced driver assistance system (ADAS). A vision-based touch-less hand gesture recognition system is proposed here for in-car human-machine interfaces (HMI). The performance of such systems is unreliable under ambient illumination conditions, which change during the course of the day. Thus, the main focus of this work was to design a system that is robust towards changing lighting conditions. For this purpose, a homomorphic filter with adaptive thresholding binarization is used. Also, gray-level edge-based segmentation ensures that it is generalized for users of different skin tones and background colors. This work was validated on selected gestures from the Cambridge Hand Gesture Database captured in five sets of non-uniform illumination conditions that closely resemble in-car illumination conditions, yielding an overall system accuracy of 91%, an average frame-by-frame accuracy of 81.38%, and a latency of 3.78 milliseconds. A prototype of the proposed system was implemented on a Raspberry Pi 3 interface together with an Android application, which demonstrated its suitability for non-critical in-car interfaces like infotainment systems.
A Combination of Inverted LSB, RSA, and Arnold Transformation to get Secure and Imperceptible Image Steganography Edi Jaya Kusuma; Christy Atika Sari; Eko Hari Rachmawanto; De Rosal Ignatius Moses Setiadi
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.1

Abstract

Securing images can be achieved using cryptography and steganography. Combining both techniques can improve the security of images. Usually, Arnold's transformation (ACM) is used to encrypt an image by randomizing the image pixels. However, applying only a transformation algorithm is not secure enough to protect the image. In this study, ACM was combined with RSA, another encryption technique, which has an exponential process that uses large numbers. This can confuse attackers when they try to decrypt the cipher images. Furthermore, this paper also proposes combing ACM with RSA and subsequently embedding the result in a cover image with inverted two-bit LSB steganography, which replaces two bits in the bit plane of the cover image with message bits. This modified steganography technique can provide twice the capacity of the previous method. The experimental result was evaluated using PSNR and entropy as the parameters to obtain the quality of the stego images and the cipher images. The proposed method produced a highest PSNR of 57.8493 dB and entropy equal to 7.9948.
Word Embedding for Rhetorical Sentence Categorization on Scientific Articles Ghoziyah Haitan Rachman; Masayu Leylia Khodra; Dwi Hendratmo Widyantoro
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.2.5

Abstract

A common task in summarizing scientific articles is employing the rhetorical structure of sentences. Determining rhetorical sentences itself passes through the process of text categorization. In order to get good performance, some works in text categorization have been done by employing word embedding. This paper presents rhetorical sentence categorization of scientific articles by using word embedding to capture semantically similar words. A comparison of employing Word2Vec and GloVe is shown. First, two experiments are evaluated using five classifiers, namely Naïve Bayes, Linear SVM, IBK, J48, and Maximum Entropy. Then, the best classifier from the first two experiments was employed. This research showed that Word2Vec CBOW performed better than Skip-Gram and GloVe. The best experimental result was from Word2Vec CBOW for 20,155 resource papers from ACL-ARC, features from Teufel and the previous label feature. In this experiment, Linear SVM produced the highest F-measure performance at 43.44%.
Cover JICTRA Vol. 12 No. 2, 2018 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 12 No. 2 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

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