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Journal of ICT Research and Applications Vol. 18 Issue 2 2024

Vol. 18 No. 2 (2024)

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Articles Published in This Issue

Explore peer-reviewed research articles published in this issue.

researchpp. 108–129

LoVi App: Android Application-based Image Classification for Low Vision

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…

Keywords
convolutional neural network deep learning image classification low vision smartphone
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researchpp. 130–142

Enhancing Skin Disease Diagnosis Through Fine-Tune Convolutional Neural Network: A Comparative Study with Multi-class Approach

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…

Keywords
fine-tune imbalance data medical imaging skin disease Xception
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researchpp. 143–154

saLFIA: Semi-automatic Live Feeds Image Annotation Tool for Vehicle Classification Dataset

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…

Keywords
annotation tool CCTV dataset vehicle classification YOLO SSD
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researchpp. 155–174

X-Band Metasurface EM Wave Absorber using SRR and Stripline: Model, Design and Implementation

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…

Keywords
free space measurement horn antenna normalized absorption SRR with stripline x-band wave absorber
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researchpp. 81–92

Virtual Reality (VR) Method to Improve Sense of Place for Interior Design Studio Students

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…

Keywords
immersive learning interior design studio sense of place virtual reality visual method design
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researchpp. 93–107

A Multivariate Fuzzy Weighted K-Modes Algorithm with Probabilistic Distance for Categorical Data

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…

Keywords
categorical data fuzzy clustering gini impurity MFWKM-PD probabilistic distance
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