Article Per Year (5 Year)
p-Index From 2020 - 2025
4.908
P-Index
This Author published in this journals
All Journal Jurnal Simetris JOIV : International Journal on Informatics Visualization Emerging Science Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Informasi MURA Journal of Information Systems and Informatics APTIKOM Journal on Computer Science and Information Technologies (CSIT) IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences Jurnal Bina Komputer Dikdimas : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknologi Informasi Mura
Kurniawan, Tri Basuki
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences Other

Published : 36 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 21 Documents
Search
Journal : Journal of Applied Data Sciences

 1   2   3 
Progressive Massive Fibrosis Detection Using Generative Adversarial Networks and Long Short-Term Memory Irianto, Suhendro Y.; Karnila, Sri; Hasibuan, M.S.; Dewi, Deshinta Arrova; Kurniawan, Tri Basuki; Kurniawan, Hendra
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.707

Abstract

Contribution: Progressive Massive Fibrosis (PMF) is a severe form of pneumoconiosis, affecting individuals exposed to mineral dust, such as coal miners and workers in the artificial stone industry. This condition causes significant pulmonary impairment and increased mortality. Early and accurate detection is vital for effective management, yet traditional diagnostic methods face challenges in differentiating PMF from other pulmonary diseases due to variability in clinical presentations and limitations in imaging techniques. Idea: The study introduces a novel diagnostic framework that integrates Generative Adversarial Networks (GAN) and Long Short-Term Memory (LSTM) networks to enhance the detection and monitoring of PMF. The GAN generates high-fidelity synthetic imaging data to address the issue of limited datasets, while the LSTM network captures temporal patterns in patient data, enabling real-time monitoring of disease progression. Objective: The primary objective of this research is to develop an AI-driven model that improves the accuracy and efficiency of PMF detection and monitoring, facilitating early diagnosis and better treatment planning. Findings: The integrated GAN-LSTM model significantly outperformed traditional diagnostic methods. It proved high accuracy, a Dice coefficient of 0.85, and an Area Under the Curve (AUC) of 0.92, showing precise differentiation of PMF from other pulmonary conditions, such as lung cancer and tuberculosis. Results: The GAN-LSTM framework achieved an accuracy of 91.3%, suggesting that the fusion of GAN and LSTM technologies can effectively address the challenges of limited datasets and heterogeneous disease progression. The model showed promise in enhancing the non-invasive detection and ongoing monitoring of PMF. Novelty: This research stands for a significant advancement in PMF diagnostics by combining GAN and LSTM technologies in a single framework. This approach improves diagnostic accuracy and eases continuous disease monitoring, offering a non-invasive and highly precise solution for PMF detection.
Co-Authors - Kurniawan, - Adi Wijaya Agus Riyanto Alde Alanda, Alde Alqudah, Mashal Kasem Alqudah, Musab Kasim Andri Andri Antoni, Darius Armoogum, Sheeba Armoogum, Vinaye Asro, Asro Astried, Astried Aziz, RZ. Abdul Azmi, Nurhafifi Binti Bappoo, Soodeshna Batumalay, Malathy Bujang, Nurul Shaira Binti Chandra, Anurag Dedy Syamsuar Dewi, Deshinta Arrova Dewi, Deshinta Arrowa Diana Diana Edi Surya Negara Eko Risdianto Fadly Fadly Fatoni, Fatoni Febriyanti Panjaitan Firosha, Ardian Fuad, Eyna Fahera Binti Eddie Habib, Shabana Hadi Syahputra Hanan, Nur Syuhana binti Abd Hasibuan, M.S. Henderi . Hendra Kurniawan Herdiansyah, M. Izman Hidayani, Nieta Hisham, Putri Aisha Athira binti Irianto, Suhendro Y. Irwansyah Irwansyah Ismail, Abdul Azim Bin Isnawijaya, Isnawijaya Joan Angelina Widians, Joan Angelina Kijsomporn, Jureerat Kurniawan, Dendi Lexianingrum, Siti Rahayu Pratami M Said Hasibuan Madjid, Fadel Muhammad Maizary, Ary Mantena, Jeevana Sujitha Mashal Alqudah Melanie, Nicolas Misinem, Misinem Mohd Salikon, Mohd Zaki Motean, Kezhilen Muhamad Akbar Muhammad Islam, Muhammad Muhammad Nasir Muhayeddin, Abdul Muniif Mohd Nathan, Yogeswaran Nazmi, Che Mohd Alif Oktariansyah Oktariansyah, Oktariansyah Onn, Choo Wou Periasamy, Jeyarani Prahartiningsyah, Anggari Ayu Praveen, S Phani Puspitasari, Novianti Qisthiano, M Riski R Rizal Isnanto Rahmi Rahmi RR. Ella Evrita Hestiandari Saksono, Prihambodo Hendro Saringat, Zainuri Singh, Harprith Kaur Rajinder Sirisha, Uddagiri Sri Karnila Sulaiman, Agus Sunda Ariana, Sunda Suriani, Uci Syaputra, Hadi Taqwa, Dwi Muhammad Thinakaran, Rajermani Triloka, Joko Udariansyah, Devi Usman Ependi Wibaselppa, Anggawidia Yeh, Ming-Lang Yorman Yupika Maryansyah, Yupika Zakari, Mohd Zaki Zakaria, Mohd Zaki