cover
Filter by Year
Journal of ICT Research and Applications
S1
Sinta Score
ISSN : -     EISSN : -
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. Abstracts and articles published on Journal of ICT Research and Applications are available online at ITB Journal and indexed by Scopus, Google Scholar, Directory of Open Access Journals, NewJour, Open J-Gate, Electronic Library University of Regensburg, EBSCO Open Science Directory, International Association for Media and Communication Research (IAMCR), Cabells Directories, Zurich Open Repository and Archive Journal Database, and ISJD-Indonesian Institute of Sciences. Publication History Formerly known as: ITB Journal of Information and Communication Technology (2007 – 2012)
Articles
169
Articles
Performance Analysis of BigDecimal Arithmetic Operation in Java

Tarigan, Jos Timanta ( Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Jalan Universitas No.9, Padang Bulan, Medan Baru, Kota Medan 20222, Sumatera Utara ) , Zamzami, Elviawaty M. ( Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Jalan Universitas No.9, Padang Bulan, Medan Baru, Kota Medan 20222, Sumatera Utara ) , Ginting, Cindy Laurent ( Faculty of Computer Science and Information Technology, Universitas Sumatera Utara, Jalan Universitas No.9, Padang Bulan, Medan Baru, Kota Medan 20222, Sumatera Utara, )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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.

Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas)

Hipiny, Irwandi ( Faculty of Computer Science and Information Technology, UNIMAS, Jalan Datuk Mohammad Musa, 94300 Kota Samarahan, Sarawak, ) , Ujir, Hamimah ( Faculty of Computer Science and Information Technology, UNIMAS, Jalan Datuk Mohammad Musa, 94300 Kota Samarahan, Sarawak, ) , Mujahid, Aazani ( Faculty of Resource Science and Technology, UNIMAS, Jalan Datuk Mohammad Musa, 94300 Kota Samarahan, Sarawak, ) , Yahya, Nurhartini Kamalia ( Danau Girang Field Centre, Sabah Wildlife Department and Cardiff University, Lower Kinabatangan Wildlife Sanctuary, Sabah, )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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%. 

A Hierarchical Emotion Classification Technique for Thai Reviews

Charoensuk, Jirawan ( Graduate School of Applied Statistics, National Institute of Development Administration, 118 Seri-Thai Road, Bangkapi, Bangkok, 10240, ) , Sornil, Ohm ( Graduate School of Applied Statistics, National Institute of Development Administration, 118 Seri-Thai Road, Bangkapi, Bangkok, 10240, )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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.

DT-MSOF Strategy and its Application to Reduce the Number of Operations in AHP

Yulianto, Fazmah Arif ( School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, ) , Kuspriyanto, Kuspriyanto ( School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, ) , Suharsono, Teguh Nurhadi ( School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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

Al-Shaikh, Ala'a ( Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman ) , Khattab, Hebatallah ( Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman ) , Al-Sharaeh, Saleh ( Department of Computer Science, King Abdulla II School for Information Technology, University of Jordan, Amman )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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

Jose, Edwin K ( Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, ) , Veni, S. ( Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, )

Journal of ICT Research and Applications Vol 12, No 3 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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.

A Combination of Inverted LSB, RSA, and Arnold Transformation to get Secure and Imperceptible Image Steganography

Kusuma, Edi Jaya ( Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol 207, 50131 Semarang, ) , Sari, Christy Atika ( Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol 207, 50131 Semarang, ) , Rachmawanto, Eko Hari ( Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol 207, 50131 Semarang, ) , Setiadi, De Rosal Ignatius Moses ( Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol 207, 50131 Semarang, )

Journal of ICT Research and Applications Vol 12, No 2 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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.

Optimization of Spaced K-mer Frequency Feature Extraction using Genetic Algorithms for Metagenome Fragment Classification

Pekuwali, Arini ( Department of Informatics Engineering, Faculty of Science and Engineering, Universitas Kristen Wira Wacana, Jalan R. Suprapto No. 35, Prailiu, Waingapu, Sumba Timur, 87113, ) , Kusuma, Wisnu Ananta ( Department of Computer Science, Faculty of Mathematics and Natural Science, Bogor Agricultural University, Jalan Meranti, Kampus IPB Darmaga, Bogor 16680, ) , Buono, Agus ( Department of Computer Science, Faculty of Mathematics and Natural Science, Bogor Agricultural University, Jalan Meranti, Kampus IPB Darmaga, Bogor 16680, )

Journal of ICT Research and Applications Vol 12, No 2 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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. 

Which Tech Will I Use? Trends in Students’ Use and Ownership of Technology in a Thai University, an Ongoing Study

Gulateee, Yuwanuch ( Nakhonphanom University, Thailand, Adjunct Edith Cowan University, 270 Joondalup Drive, Joondalup WA 6027, ) , Pagram, Jeremy ( A CSaLT, Edith Cowan University, 2 Bradford St, Mt Lawley, WA, 6050 ) , Combes, Babara ( Charles Sturt University, Boorooma St, North Wagga Wagga NSW 2650, )

Journal of ICT Research and Applications Vol 12, No 2 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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

Anant, Shalini ( Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112 ) , Veni, Shanmugham ( Department of Electronics and Communication Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112 )

Journal of ICT Research and Applications Vol 12, No 2 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Original Source | Check in Google Scholar |

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.