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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 302 Documents
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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.
Using Cultural and Social Beliefs in Language Games Theerapol Limsatta; Ohm Sornil
Journal of ICT Research and Applications Vol. 10 No. 3 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.3.5

Abstract

Agreement on word-object pairing in communication depends on the intensity of the beliefs that gradually emerge in a society of agents, on the condition that no one was born with embedded knowledge. The agents search and exchange ideas about unknown word-object pairings, until they meet a consensus about what the object should be named. A language game is a social process of finding agreement on word-object pairings through communication in a multi-agent system. In this paper, a technique is proposed to discover the association between a word and the agents' beliefs on an object using self-organizing maps and a cultural algorithm in a multi-hearer environment. A conceptual space is implemented, which stores the agent's beliefs in three dimensions, represented by colors. The technique was evaluated for a variety of scenarios using four significant measures: coherence, specificity, success rate, and word size. The results showed that with the proposed method social agents can reach agreement fast and that their communication is effective.
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).
Document Grouping by Using Meronyms and Type-2 Fuzzy Association Rule Mining Fahrur Rozi; Farid Sukmana
Journal of ICT Research and Applications Vol. 11 No. 3 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.3.4

Abstract

The growth of the number of textual documents in the digital world, especially on the World Wide Web, is incredibly fast. This causes an accumulation of information, so we need efficient organization to manage textual documents. One way to accurately classify documents is using fuzzy association rules. The quality of the document clustering is affected by phase extraction of key terms and type of fuzzy logic system (FLS) used for clustering. The use of meronyms in the extraction of key terms to obtain cluster labels helps obtaining meaningful cluster labels and in addition ambiguities and uncertainties that occur in the rules of type-1 fuzzy logic systems can be overcome by using type-2 fuzzy sets. This study proposes a method of key term extraction based on meronyms with an initialization cluster using fuzzy association rule mining for document clustering. This method consists of four stages, i.e. preprocessing of the document, extraction of key terms with meronyms, extraction of candidate clusters, and cluster tree construction. Testing of this method was done with three different datasets: classic, Reuters, and 20 Newsgroup. Testing was done by comparing the overall F-measure of the method without meronyms and with meronyms. Based on the testing, the method with meronyms in the extraction of keywords produced an overall F-measure of 0.5753 for the classic dataset, 0.3984 for the Reuters dataset, and 0.6285 for the 20 Newsgroup dataset.
Simulating Shopper Behavior using Fuzzy Logic in Shopping Center Simulation Jason Christian; Seng Hansun
Journal of ICT Research and Applications Vol. 10 No. 3 (2016)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2016.10.3.6

Abstract

To simulate real-world phenomena, a computer tool can be used to run a simulation and provide a detailed report. By using a computer-aided simulation tool, we can retrieve information relevant to the simulated subject in a relatively short time. This study is an extended and complete version of an initial research done by Christian and Hansun and presents a prototype of a multi-agent shopping center simulation tool along with a fuzzy logic algorithm implemented in the system. Shopping centers and all their components are represented in a simulated 3D environment. The simulation tool was created using the Unity3D engine to build the 3D environment and to run the simulation. To model and simulate the behavior of agents inside the simulation, a fuzzy logic algorithm that uses the agents' basic knowledge as input was built to determine the agents' behavior inside the system and to simulate human behaviors as realistically as possible.
Rainfall Prediction in Tengger, Indonesia Using Hybrid Tsukamoto FIS and Genetic Algorithm Method Ida Wahyuni; Wayan Firdaus Mahmudy
Journal of ICT Research and Applications Vol. 11 No. 1 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.1.3

Abstract

Countries with a tropical climate, such as Indonesia, are highly dependent on rainfall prediction for many sectors, such as agriculture, aviation, and shipping. Rainfall has now become increasingly unpredictable due to climate change and this phenomenon also affects Indonesia. Therefore, a robust approach is required for more accurate rainfall prediction. The Tsukamoto Fuzzy Inference System (FIS) is one of the algorithms that can be used for prediction problems, but if its membership functions are not specified properly, the prediction error is still high. To improve the results, the boundaries of the membership functions can be adjusted automatically by using a genetic algorithm. The proposed genetic algorithm employs two selection processes. The first one uses the Roulette wheel method to select parents, while the second one uses the elitism method to select chromosomes for the next generation. Based on this approach, a rainfall prediction experiment was conducted for Tengger, Indonesia using historical rainfall data for ten-year periods. The proposed method generated root mean square errors (RMSE) of 6.78 and 6.63 for the areas of Tosari and Tutur respectively. These results are better compared with the results using Tsukamoto FIS and the Generalized Space Time Autoregressive (GSTAR) model from previous studies.
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.
Improvement of Fuzzy Geographically Weighted Clustering-Ant Colony Optimization Performance using Context-Based Clustering and CUDA Parallel Programming Nila Nurmala; Ayu Purwarianti
Journal of ICT Research and Applications Vol. 11 No. 1 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.1.2

Abstract

Geo-demographic analysis (GDA) is the study of population characteristics by geographical area. Fuzzy Geographically Weighted Clustering (FGWC) is an effective algorithm used in GDA. Improvement of FGWC has been done by integrating a metaheuristic algorithm, Ant Colony Optimization (ACO), as a global optimization tool to increase the clustering accuracy in the initial stage of the FGWC algorithm. However, using ACO in FGWC increases the time to run the algorithm compared to the standard FGWC algorithm. In this paper, context-based clustering and CUDA parallel programming are proposed to improve the performance of the improved algorithm (FGWC-ACO). Context-based clustering is a method that focuses on the grouping of data based on certain conditions, while CUDA parallel programming is a method that uses the graphical processing unit (GPU) as a parallel processing tool. The Indonesian Population Census 2010 was used as the experimental dataset. It was shown that the proposed methods were able to improve the performance of FGWC-ACO without reducing the clustering quality of the original method. The clustering quality was evaluated using the clustering validity index.
A Comprehensive Performance Analysis of IEEE 802.11p based MAC for Vehicular Communications Under Non-saturated Conditions Akram A. Abdullah Almohammedi; Nor K. Noordin; Aduwati Sali; Fazirulhisyam Hashim; Sabri Saeed
Journal of ICT Research and Applications Vol. 11 No. 1 (2017)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2017.11.1.6

Abstract

Reliable and efficient data broadcasting is essential in vehicular networks to provide safety-critical and commercial service messages on the road. There is still no comprehensive analysis of IEEE 802.11p based MAC that portrays the presence of buffer memory in vehicular networks. Besides, most of the analytical works do not fulfill some of the IEEE 802.11p specifications, such as short retry limit and back-off timer freezing. This paper proposes a 1-D and 2-D Markov model to analyze mathematically IEEE 802.11p based MAC for safety and non-safety messages respectively. The work presented in this paper takes into account the traffic arrival along with the first-order buffer memory and freezing of the back-off timer as well, to utilize the channel efficiently and provide higher accuracy in estimation of channel access, yielding more precise results of the system throughput for non-safety messages and lower delay for safety messages. Furthermore, back-off stages with a short retry limit were applied for non-safety messages in order to meet the IEEE 802.11p specifications, guaranteeing that no packet is served indefinitely, avoiding the overestimation of system throughput. A simulation was carried out to validate the analytical results of our model.

Page 16 of 31 | Total Record : 302

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