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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. 12 No. 3 (2018)" : 7 Documents clear
DT-MSOF Strategy and its Application to Reduce the Number of Operations in AHP Fazmah Arif Yulianto; Kuspriyanto Kuspriyanto; Teguh Nurhadi Suharsono
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.3

Abstract

A computing strategy called Double Track"“Most Significant Operation First (DT-MSOF) is proposed. The goal of this strategy is to reduce computation time by reducing the number of operations that need to be executed, while maintaining a correct final result. Executions are conducted on a sequence of computing operations that have previously been sorted based on significance. Computation will only run until the result meets the needs of the user. In this study, the DT-MSOF strategy was used to modify the Analytic Hierarchy Process (AHP) algorithm into MD-AHP in order to reduce the number of operations that need to be done. The conventional AHP uses a run-to-completion approach, in which decisions can only be obtained after all of the operations have been completed. On the other hand, the calculations in MD-AHP are carried out iteratively only until the conditions are reached where a decision can be made. The simulation results show that MD-AHP can reduce the number of operations that need to be done to obtain the same results (decisions) as obtained by conventional AHP. It was also found that the more uneven the distribution of priority values, the more the number of operations could be reduced.  
Performance Comparison of LEACH and LEACH-C Protocols in Wireless Sensor Networks Ala'a Al-Shaikh; Hebatallah Khattab; Saleh Al-Sharaeh
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.2

Abstract

Wireless Sensor Networks (WSNs) draw the attention of researchers due to the diversity of applications that use them. Basically, a WSN comprises many sensor nodes that are supplied with power by means of a small battery installed in the node itself; the node can also be self-charged by a solar cell. Sometimes it is impossible to change the power supply of battery-operated nodes. This dictates that sensor nodes must utilize the energy they have in an optimal manner. Data communication is the main cause of energy dissipation. In this context, designing protocols for WSNs demands more attention to the design of energy-efficient routing protocols that allow communications between sensor nodes and their base station (BS) with the least cost. LEACH is a prominent hierarchical cluster-based routing protocol. It groups sensor nodes into clusters to reduce energy dissipation. On the other hand, LEACH-C is a protocol based on LEACH that claims to improve energy dissipation over LEACH. In this paper, a successful attempt was made to compare these two protocols using MATLAB. The results show that LEACH-C has better performance than LEACH in terms of power dissipation.
Vacant Parking Lot Information System Using Transfer Learning and IoT Edwin K Jose; S. Veni
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.1

Abstract

Parking information systems have become very important, especially in metropolitan areas as they help to save time, effort and fuel when searching for parking. This paper offers a novel low-cost deep learning approach to easily implement vacancy detection at outdoor parking spaces with CCTV surveillance. The proposed method also addresses issues due to perspective distortion in CCTV images. The architecture consists of three classifiers for checking the availability of parking spaces. They were developed on the TensorFlow platform by re-training MobileNet (a pre-trained Convolutional Neural Network (CNN)) model using the transfer learning technique. A performance analysis showed 88% accuracy for vacancy detection. An end-to-end application model with Internet of Things (IoT) and an Android application is also presented. Users can interact with the cloud using their Android application to get real-time updates on parking space availability and the parking location. In the future, an autonomous car could use this system as a V2I (Vehicle to Infrastructure) application in deciding the nearest parking space.
Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas) Irwandi Hipiny; Hamimah Ujir; Aazani Mujahid; Nurhartini Kamalia Yahya
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.4

Abstract

Passive biometric identification enables wildlife monitoring with minimal disturbance. Using a motion-activated camera placed at an elevated position and facing downwards, images of sea turtle carapaces were collected, each belonging to one of sixteen Chelonia mydas juveniles. Then, co-variant and robust image descriptors from these images were learned, enabling indexing and retrieval. In this paper, several classification results of sea turtle carapaces using the learned image descriptors are presented. It was found that a template-based descriptor, i.e. Histogram of Oriented Gradients (HOG) performed much better during classification than keypoint-based descriptors. For our dataset, a high-dimensional descriptor is a must because of the minimal gradient and color information in the carapace images. Using HOG, we obtained an average classification accuracy of 65%. 
Performance Analysis of BigDecimal Arithmetic Operation in Java Jos Timanta Tarigan; Elviawaty M. Zamzami; Cindy Laurent Ginting
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.5

Abstract

The Java programming language provides binary floating-point primitive data types such as float and double to represent decimal numbers. However, these data types cannot represent decimal numbers with complete accuracy, which may cause precision errors while performing calculations. To achieve better precision, Java provides the BigDecimal class. Unlike float and double, which use approximation, this class is able to represent the exact value of a decimal number. However, it comes with a drawback: BigDecimal is treated as an object and requires additional CPU and memory usage to operate with. In this paper, statistical data are presented of performance impact on using BigDecimal compared to the double data type. As test cases, common mathematical processes were used, such as calculating mean value, sorting, and multiplying matrices.
A Hierarchical Emotion Classification Technique for Thai Reviews Jirawan Charoensuk; Ohm Sornil
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2018.12.3.6

Abstract

Emotion classification is an interesting problem in affective computing that can be applied in various tasks, such as speech synthesis, image processing and text processing. With the increasing amount of textual data on the Internet, especially reviews of customers that express opinions and emotions about products. These reviews are important feedback for companies. Emotion classification aims to identify an emotion label for each review. This research investigated three approaches for emotion classification of opinions in the Thai language, written in unstructured format, free form or informal style. Different sets of features were studied in detail and analyzed. The experimental results showed that a hierarchical approach, where the subjectivity of the review is determined first, then the polarity of opinion is identified and finally the emotional label is calculated, yielded the highest performance, with precision, recall and F-measure at 0.691, 0.743 and 0.709, respectively.
Cover JICTRA Vol. 12 No. 3, 2018 Journal of ICT Research and Applications
Journal of ICT Research and Applications Vol. 12 No. 3 (2018)
Publisher : LPPM ITB

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

Abstract

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