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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) KAPAL Jurnal Ilmu Pengetahuan dan Teknologi Kelautan SITEKIN: Jurnal Sains, Teknologi dan Industri Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Tri Dharma Mandiri: Diseminasi dan Hilirisasi Riset Kepada Masyarakat (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika
Kurnianingtyas, Diva
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Public Health Social Sciences Other

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Journal : joiv international journal on informatics visualization

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Chest X-Ray Images Clustering using Convolutional Autoencoder for Lung Disease Detection Syafira, Putri Amanda; Yudistira, Novanto; Kurnianingtyas, Diva
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2478

Abstract

In healthcare, medical imaging is commonly used for health assessments. One of the most commonly used types of medical imaging is X-ray imaging. One area that often undergoes examination using this modality is the lungs, where healthcare professionals use X-ray images to interpret the results. However, prolonged interpretation of X-ray results by healthcare professionals and other work activities can lead to errors and potentially result in invalid disease identification. There is a need for a system that can classify the detection results from these images to assist healthcare professionals in their tasks. Various methods can be used for this purpose, such as classification, clustering, segmentation, etc. However, data labeling requires significant resources and costs, especially with large-scale datasets. One possible solution is to use an unsupervised learning approach to address this. One method under unsupervised learning is clustering, which allows the system to process and understand data patterns without needing external annotations or manual labeling. This research uses an autoencoder as a subcategory of unsupervised learning. This is because autoencoders can automatically extract relevant features from the data without needing external label guidance. The research utilizes a dataset consisting of 700 X-ray images of the chest, including 500 images showing disease and 200 normal X-ray images. This research aims to determine the effectiveness of clustering methods using an autoencoder model in grouping X-ray image results. The research conducted two experiments. In the first experiment, an autoencoder with 18 Layers was used, resulting in the best performance with a value of K=15 and a rand index of 76%. In the second experiment, an autoencoder with a reduced number of Layers (11 Layers) was used, and it achieved the best performance with a value of K=15 and a rand index of 87%.
Co-Authors Abilo, Steven Hansel Adimoelja, Ariawan Adzra, Puti Narita Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Almira Syawli Alrum, Chaizhar Zaky Anam, Muhammad Haris Khoirul Arief Andy Soebroto Ayu Wulandari, Beby Bajsair, Fath' Hani Sarli Bayu Priyambadha Bayu Rahayudi Candra Dewi Chandra Saputra, Mochamad Cindy Taurusta Darma Setiawan, Budi Daud, Nathan Dian Purnamasari Dimas Kurniawan Dyan Putri Mahardika, Dyan Putri Edy Santoso Eko Sakti Pramukantoro, Eko Sakti Emery Razan, Ghatfan Fabiano, Stefanus Fadilah Mi'roj, Muhammad Geoffrey Manurung, Daniel Hanggara, Buce Trias Hanif, Haidar Huda, Fais Al Ika Amalia Kartika Imam Cholissodin Indriati Indriati Indriati Inggit Marodiyah K., Dwi Angraeni Karsanto, Daniel Gifted Kirana, Naufal Laksana Kohei Arai Lailil Muflikhah Latuputty, Yosua Nathanael M. Fajar, M. Mahmudy, Wayan Marji Marji Mauluda Wildani, Barik Mohammad Fauzi Mohammad, Luthfansyah Muh. Arif Rahman Muhammad Luqman Hakim Muhammad Mulyadi, Muhammad Mukhrodi, Dillah Lyra Naldi, Jupri Naufal, Muhammad Jilan Novanto Yudistira Pandu Syahfitra, Dian Pradana, Andika Irza Pramesthi, Nisriina Dyan Prasetyo, Dimas Fajar Pratama, Aditya Rizki Prima Zulvarina, Prima Putra, I Gusti Ngurah Mayun Suryatama Giri Rahadi, Cakra W.K. Rahadi, Shinta J.A. Rahardian, Brillian Aristyo Ramadhan, Ahmad Irham Ramadhan, Mohammad Haikal Ramadhan, Noval Raihan Rina Rina Riswan Septriayadi Sianturi Rudianto, Amadeo Muhammad Augie Sari, Indah Apriliana Satrio Agung Wicaksono Soebroto, Arief Andi Sukma, Lintang Cahyaning Syafira, Putri Amanda Tibyani Trias Hanggara, Buce Tusty Nadia Maghfira, Tusty Nadia Virliani, Putri Wayan Firdaus Mahmudy Yulfani, R. D.