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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
 1 
Search results for , issue "Vol. 11 No. 2 (2017)" : 7 Documents clear
A Chemical Reaction Optimization Approach to Prioritize the Regression Test Cases of Object-Oriented Programs Sudhir Kumar Mohapatra; Srinivas Prasad
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.1

Abstract

Regression test case prioritization is used to improve certain performance goals. Limited resources force to choose an effective prioritization technique, which makes an ordering of the test cases so that the most suitable test case will be executed first. Executing regression test cases for a fixed time is all about time aware test case prioritization. Regression test case prioritization using chemical reaction optimization (CRO) for object-oriented programs is proposed in this paper. The effectiveness of the test case ordering was measured using average percentage of faults detected (APFD). Experiments on three object-oriented subject programs involving three different techniques were performed to judge the proposed approach. The empirical results indicate that the algorithm implemented using CRO gives a higher APFD value than the other two techniques.
Passive Available Bandwidth Estimation Based on Collision Probability and Node State Synchronization in Wireless Networks Adhi Rizal; Yoanes Bandung
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.2

Abstract

In wireless networks, available bandwidth estimation is challenging because wireless channels are used by multiple users or applications concurrently. In this study, we propose a passive measurement scheme to estimate the available bandwidth in 802.12 wireless networks based on the combination and modification of two existing schemes, Distributed Lagrange Interpolation Based Available Bandwidth Estimation (DLI-ABE) and Accurate Passive Bandwidth Estimation (APBE). The proposed scheme uses the channel busy state, which is affected by transmitting or receiving processes caused by carrier sensing. Therefore, the sender and the receiver node should be synchronized using various states that can be affected by other nodes. Moreover, the proposed scheme was developed with the involvement of relevant calculation of possible overhead caused by control messaging that occurs in the Media Access Control (MAC) layer and collision probability caused by data flow from hidden nodes. The result showed that the proposed scheme can estimate the available bandwidth of wireless networks more accurately than DLI-ABE and APBE.
Performance Improvement of LeastSquares Adaptive Filter for High-Speed Train Communication Systems Irma Zakia; Adit Kurniawan
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.3

Abstract

The downlink communication channel from high-altitude platform (HAP) to high-speed train (HST) in the Ka-band is a slowly time-varying Rician distributed flat fading channel with 10-25 dB Rician K factor. In this respect, the received signal is mainly affected by the Doppler shift of the line-of-sight (LOS) link. In order to increase receiver performance, we propose to firstly compensate the Doppler shift of the received signal before least-squares (LS) adaptive filtering is pursued. Implementing the proposed method requires a priori knowledge of the time-varying phase of the LOS component. This is justified since signalling between the train and the controller exists such that the train velocity and location are predictable. Implementing the proposed method to the recursive LS (RLS) received beamforming algorithm shows reduction of mean square error (MSE) and bit error rate (BER).
A Comprehensive Survey of Data Mining Techniques on Time Series Data for Rainfall Prediction Neelam Mishra; Hemant Kumar Soni; Sanjiv Sharma; A.K. Upadhyay
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.4

Abstract

Time series data available in huge amounts can be used in decision-making. Such time series data can be converted into information to be used for forecasting. Various techniques are available for prediction and forecasting on the basis of time series data. Presently, the use of data mining techniques for this purpose is increasing day by day. In the present study, a comprehensive survey of data mining approaches and statistical techniques for rainfall prediction on time series data was conducted. A detailed comparison of different relevant techniques was also conducted and some plausible solutions are suggested for efficient time series data mining techniques for future algorithms. 
Hybrid Neural Network and Linear Model for Natural Produce Recognition Using Computer Vision Joko Siswantoro; Anton Satria Prabuwono; Azizi Abdullah; Bahari Indrus
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.5

Abstract

Natural produce recognition is a classification problem with various applications in the food industry. This paper proposes a natural produce recognition method using computer vision. The proposed method uses simple features consisting of statistical color features and the derivative of radius function. A hybrid neural network and linear model based on a Kalman filter (NN-LMKF) was employed as classifier. One thousand images from ten categories of natural produce were used to validate the proposed method by using 5-fold cross validation. The experimental result showed that the proposed method achieved classification accuracy of 98.40%. This means it performed better than the original neural network and k-nearest neighborhood.
A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition Bilal Bataineh
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.2.6

Abstract

Document image analysis and recognition are important topics in the field of artificial intelligence. In this context, the availability of a database with good script samples is an important requirement for machine-learning processes. For Latin and Asian languages many suitable databases exist. However, there is a shortage of databases with Arabic samples. In this work, a new database of printed Arabic text is introduced. The new concept of collecting sub-words (PAWs) instead of words or individual character samples was adopted. These PAWs constitute all words in the Arabic language. The collected database consists of 83,056 images of PAWs extracted from approximately 550,000 different words. Each sample is presented in the database in five font types: Thuluth, Naskh, Andalusi, Typing Machine, and Kufi. In total, the database consists of 415,280 images. Moreover, ground truth information is included with each PAW image to describe its occurrence number, occurrence frequency, positions and the shapes of the characters. This paper presents a statistical analysis of the frequency of each PAW in the Arabic language.
Cover JICTRA Vol. 11 No. 2, 2017 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 11 No. 2 (2017)
Publisher : LPPM ITB

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

Abstract

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