https://journals.itb.ac.id/index.php/jictra/issue/feedJournal of ICT Research and Applications2024-10-07T10:29:21+07:00Dr. Eng. Achmad Munirjictra@itb.ac.idOpen Journal Systems<p><img class="imgdesc" src="https://lppm.itb.ac.id/wp-content/uploads/sites/55/2021/08/JICTRA_ITB_small.png" alt="" /></p> <p style="text-align: justify;"><em>Journal of ICT Research and Applications</em> 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.</p> <p style="text-align: justify;">Abstracts and articles published on Journal of ICT Research and Applications are available online at ITB Journal and indexed by <a href="https://www.scopus.com/sourceid/21100268428?origin=resultslist">Scopus</a>, <a href="https://scholar.google.co.id/citations?user=kv2tyQIAAAAJ&hl=id">Google Scholar</a>, <a href="https://doaj.org/toc/2338-5499?source=%7B%22query%22%3A%7B%22filtered%22%3A%7B%22filter%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22term%22%3A%7B%22index.issn.exact%22%3A%222338-5499%22%7D%7D%2C%7B%22term%22%3A%7B%22_type%22%3A%22article%22%7D%7D%5D%7D%7D%2C%22query%22%3A%7B%22match_all%22%3A%7B%7D%7D%7D%7D%2C%22from%22%3A0%2C%22size%22%3A100%7D">Directory of Open Access Journals</a>, <a href="https://rzblx1.uni-regensburg.de/ezeit/detail.phtml?bibid=AAAAA&colors=7&lang=en&jour_id=167017">Electronic Library University of Regensburg</a>, <a href="https://atoz.ebsco.com/Titles/SearchResults/8623?SearchType=Contains&Find=journal+of+ICT+RESEARCH+AND+APPLICATIONS&GetResourcesBy=QuickSearch&resourceTypeName=allTitles&resourceType=&radioButtonChanged=">EBSCO Open Science Directory</a>, <a href="https://iamcr.org/open-access-journals">International Association for Media and Communication Research (IAMCR)</a>, <a href="https://miar.ub.edu/issn/2337-5787">MIAR: Information Matrix for the Analysis of Journals Universitat de Barcelona</a>, Cabells Directories, <a href="https://www.jdb.uzh.ch/id/eprint/18193/">Zurich Open Repository and Archive Journal Database</a>, <a href="https://oaji.net/journal-detail.html?number=4569">Open Academic Journals Index</a>, Indonesian Publication Index and ISJD-Indonesian Institute of Sciences. The journal is under reviewed by Compendex, Engineering Village.</p> <p>ISSN: <a href="https://issn.brin.go.id/terbit/detail/1356660436">2337-5787</a> E-ISSN: <a href="https://issn.brin.go.id/terbit/detail/1372766667">2338-5499</a></p> <p>Reg. No. 691-SIC-UPPGT-SIT-1963, <a title="Accreditation Certificate" href="https://drive.google.com/file/d/1z2S39iDtp_BBRbz9JaCWSaShvACA7qGg/view?usp=share_link">Accreditation No. 164/E/KPT/2021</a></p> <p>Published by the Directorate for Research and Community Services, Institut Teknologi Bandung.</p> <p><span style="text-decoration: underline;"><strong>Publication History</strong></span></p> <p><strong>Formerly known as:</strong></p> <ul> <li>ITB Journal of Information and Communication Technology (2007 - 2012)</li> </ul> <p>Back issues can be read online at: https://journal.itb.ac.id</p> <p><span style="text-decoration: underline;"><strong>Scimago Journal Ranking</strong></span></p> <p><a title="SCImago Journal & Country Rank" href="https://www.scimagojr.com/journalsearch.php?q=21100268428&tip=sid&clean=0"><img src="https://www.scimagojr.com/journal_img.php?id=21100268428&title=true" alt="SCImago Journal & Country Rank" border="0" /></a></p>https://journals.itb.ac.id/index.php/jictra/article/view/22395Virtual Reality (VR) Method to Improve Sense of Place for Interior Design Studio Students2024-06-30T20:35:00+07:00Akhmadi Akhmadiakhmadi@telkomuniversity.ac.idAthifa Sri Ismirantiakhmadi@telkomuniversity.ac.idHanif Azharakhmadi@telkomuniversity.ac.idAhmad Nur Shehaakhmadi@telkomuniversity.ac.id<p>Virtual reality (VR) technology has emerged in response to recent developments in the 3-dimensional (3D) world. VR enables people to engage in various metaverse world experiences in a more immersive way. Immersive learning is a learning method that uses 3D digital technology to facilitate the learning process by visualization in the classroom. This research used a case study of the Interior Design II studio course taken by level-2 students of the Department of Interior Design, School of Creative Industries, Telkom University, Indonesia. The Interior Design II course requires students to design the interior of a residence with a minimum area of 100 m<sup>2</sup>. The method of paired sample test analysis was used to assess student’s preferences for pre-test and post-test statements from the VR intervention method in assessing student’s sense of place in the final design of the course. The results showed significant differences in student preferences during the pre-test (481.3% and 790.6%), which increased during the post-test (641.7% and 801%). The paired sample t-test analysis results also showed a Sig (2-tailed) number of 0.000 < 0.05, so there is a significant relationship between the pre-test and post-test intervention.</p>2024-09-30T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applicationshttps://journals.itb.ac.id/index.php/jictra/article/view/23258A Multivariate Fuzzy Weighted K-Modes Algorithm with Probabilistic Distance for Categorical Data2024-07-15T21:34:10+07:00Ren-Jieh Kuorjkuo@mail.ntust.edu.twMaya Cendanad10901809@mail.ntust.edu.twThi Phuong Quyen Nguyenntpquyen@dut.udn.vnFerani E. Zulviafezulvia@mail.ntust.edu.tw<p>Data clustering is a data mining approach that assigns similar data to the same group. Traditionally, cluster similarity considers all attributes equally, but in real-world applications, some attributes may be more important than others. Therefore, this study proposes an algorithm that utilizes multivariate fuzzy weighting to demonstrate the varying importance of each attribute, using a Gini impurity measure for weight assignment. Additionally, the proposed algorithm implements probabilistic distance to reduce sensitivity to noise. Probabilistic distance offers more detailed information and better interpretation than Hamming distance, which ignores attribute positions. Probabilistic distance utilizes information about the attribute’s position within and between clusters. This enhances clustering performance by creating clusters with more similar attributes. Therefore, the proposed Multivariate Fuzzy Weighted K-Modes with Probabilistic Distance for Categorical Data (MFWKM-PD) algorithm, based on the multivariate fuzzy K-modes algorithm, not only considers detailed membership calculations but also considers the varying contributions of attributes and their positions in distance calculation. This study evaluated the proposed MFWKM-PD using several benchmark datasets. The experiments validated that the proposed MFWKM-PD shows promising results compared to other algorithms in terms of accuracy, NMI, and ARI.</p>2024-09-30T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applicationshttps://journals.itb.ac.id/index.php/jictra/article/view/22132LoVi App: Android Application-based Image Classification for Low Vision2024-08-17T17:04:53+07:00Mitra Sofiyatimitrasofiyati@gmail.comFandi Azam Wiranatafandi.z.w@gmail.comWervyan Shalannandawervyan@stei.itb.ac.idEueung Mulyanaeueung@telecom.stei.itb.ac.idIsa Anshoriisaa@staff.stei.itb.ac.idArdianto Satriawanasatriawan@staff.stei.itb.ac.id<p>In Indonesia, many people with visual impairments are drawing public attention to their rights as fellow humans. One of the limitations that individuals with low vision face is their ability to recognize objects and navigate their surroundings due to difficulties in visual perception. In this modern era, deep learning technologies, especially in image classification, can help people with low vision overcome these challenges. In this paper, we discuss a deep learning system that optimizes image classification on users' smartphones to enhance visual support for individuals with low vision. We present an Android-based app, LoVi, designed to assist users with low vision. Powered by core systems within Sherpa models (TrotoarNet, IndoorNet, and CurrencyNet), LoVi has three modes: outdoor, indoor, and currency. The LoVi application provides over 80% accuracy for navigation on sidewalks, indoor object recognition, and currency identification. TrotoarNet aids in sidewalk navigation, IndoorNet assists with indoor object identification, and CurrencyNet recognizes Rupiah banknotes. Additionally, low-vision users can receive voice feedback for further accessibility.</p>2024-09-30T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applicationshttps://journals.itb.ac.id/index.php/jictra/article/view/23005Enhancing Skin Disease Diagnosis Through Fine-Tune Convolutional Neural Network: A Comparative Study with Multi-class Approach2024-08-19T09:03:30+07:00Najnin Akter Ringkyringkynajnin016@gmail.comAbu Kowshir Bittoabu.kowshir777@gmail.comKhalid Been Md. Badruzzaman Biplobkhalid@daffodilvarsity.edu.bdMd. Fazla Elaheelahe.se@daffodilvarsity.edu.bdMusabbir Hasan Sammakmusabbirhasansammak@outlook.comTapushe Rabaya Tomatoma.swe@diu.edu.bd<p>Due to their similar appearance, skin disorders frequently disguise their early warning signs from our skin, which is the defense system of the body. Preventing serious disorders requires their early detection. This work investigated the use of fine-tune transfer learning as a fast and accurate way to diagnose skin diseases. To classify different skin issues, we used pre-trained models, i.e., InceptionV3, DenseNet201, and Xception. This work examined 17,500 photos from three sources. It was found that fine-tune Xception performed exceptionally well, with an accuracy rate of 99.14%. It was closely followed by DenseNet201 and InceptionV3, each with different processing speeds, 98.74% and 98.46%, respectively. We used transfer learning with data sets validated by medical experts, outperforming earlier research in precision. This more accurate detection of skin diseases could greatly improve patient outcomes and expedite medical procedures. This approach is new in that it fine-tunes transfer learning by utilizing a vast number of data to increase accuracy compared to other researcher works.</p>2023-09-30T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applicationshttps://journals.itb.ac.id/index.php/jictra/article/view/20047saLFIA: Semi-automatic Live Feeds Image Annotation Tool for Vehicle Classification Dataset2024-08-19T09:26:29+07:00Umi Chasanahumi.chasanah@brin.go.idGilang Putragilang.mantara.putra@brin.go.idSahid Bismantokosahid.bismantoko@brin.go.idSofwan Hidayatsofwan.hidayat@brin.go.idTri Widodotriw005@brin.go.idMohammad Rosyidimros001@brin.go.id<p>Deep learning’s reliance on abundant data with accurate annotations presents a significant drawback, as developing datasets is often time-consuming and costly for specific problems. To address this drawback, we propose a semi-automatic live-feed image annotation tool called saLFIA. Our case study utilized CCTV data from Indonesia’s toll roads as one of the sources for live-feed images. The primary contribution of saLFIA is a labeling tool designed to generate new datasets from public source images, focusing on vehicle classification using YOLOv3 and SSD algorithms. The evaluation results indicated that SSD achieved higher accuracy with fewer initial images, while YOLOv3 reached maximum accuracy with larger initial datasets, resulting in 8 misdetections out of 380 objects. The saLFIA tool simplifies the annotation process, presenting a labeling tool for creating annotated datasets in a single operation. saLFIA is available at URL https://github.com/gilangmantara/salfia.</p>2024-10-21T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applicationshttps://journals.itb.ac.id/index.php/jictra/article/view/23534X-Band Metasurface EM Wave Absorber using SRR and Stripline: Model, Design and Implementation2024-10-07T10:29:21+07:00Budi Syihabuddinbudisyihab@telkomuniversity.ac.idMohammad Ridwan Effendim.ridwan.effendi@gmail.comAchmad Munirmunir@ieee.org<p>This paper presents a model, design, and implementation of a metasurface electromagnetic (EM) wave absorber for operation in the frequency range of the X-band. The model of the metasurface was constructed with a split ring resonator (SSR) and a stripline and it was designed with a single unit cell, whereby the results were approached with transmission line theory for patch impedance extraction. Implementation of a metasurface EM wave absorber was deployed on an FR4 Epoxy dielectric substrate with dimensions of 80-unit cells 80-unit cells and characterized with two horn antennas, which were connected to a signal generator as the transmitter and a spectrum analyzer as the receiver. In front of the horn antennas a device under test (DUT) was installed, i.e., a metasurface EM wave absorber and a metal plate with similar dimensions. The metal plate was expected to perform full reflection at the same distance and antenna orientation. The same condition was used as a normalization factor to optimize the absorption of the metasurface EM wave absorber. The characterization results showed that the minimum normalized absorption of the SRR and stripline at the designated measurement distances was 0.99, 0.99, 0.99, and 0.97, at frequencies of 8.85 GHz, 9.08 GHz, 9.15 GHz, and 9.10 GHz, respectively, and a antenna orientation.</p>2024-10-31T00:00:00+07:00Copyright (c) 2024 Journal of ICT Research and Applications