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Hendra Kurniawan
Institut Informatika Dan Bisnis Darmajaya
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Journal : Journal of Applied Data Sciences

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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.
SiMoI New Method to Solve the Sparsity Problem in Collaborative Filtering Kurniawan, Hendra; Lestari, Sri; Saleh, Sushanty; Satrio, Rafli Banu
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1015

Abstract

Sparsity data is a major challenge in collaborative recommendation systems, characterized by the predominance of missing values within the user-item matrix. When a substantial portion of data is unavailable, the estimation process becomes hindered, and prediction accuracy declines due to limited usable information. To address this issue, this study introduces a novel method called SiMoI (Similarity, Mode, and Minimum Imputation), which is adaptively designed to handle high levels of sparsity. The SiMoI method combines user similarity with imputation strategies based on mode and minimum values. By leveraging subsets of the most informative users and items, the method efficiently fills missing entries while maintaining prediction stability. Evaluation was conducted using both real and synthetic datasets with varying sizes and degrees of sparsity, including an extreme scenario with 93.7% missing data. Experimental results show that SiMoI consistently produces more accurate predictions than baseline methods. Under high-sparsity conditions, SiMoI achieved an RMSE as low as 0.823, outperforming KNNI (0.947) and MEAN (1.021). Moreover, SiMoI demonstrated resilience across different data scales and sparsity distributions, indicating its flexibility and scalability in diverse contexts. These findings suggest that SiMoI is an effective and stable approach for addressing sparsity and holds strong potential for implementation in user-based recommendation systems, particularly in real-world scenarios where data availability is frequently limited.
Co-Authors , Azmi , Herdianta - Nurjoko Abdi Darmawan Abdullah Merjani, Abdullah Acihmah Sidauruk Ade Moussadecq Adrin, Adrin Adytama, Muhammad Rezky Agung Pradana Agus Mulyana Agus Rahardi Ahmad Soleh Alfarihin, Alfin Alfarizi, Muhammad Amrullah, Ahmad Nur Hakim Angelina, Eleonora Anggraeni, Yessy Anggreiny, Cut Dini ANIK KUSMIATUN Anita Dewi Purwati Antoni Suseno Ardiansyah, Ardian Ardiansyah Ardiansyah, Muhamad Iqbal Arif Rahman Hakim Aritonang, Hironius Asyer Keith Ariza, Fauziah Nur Ascarya, Farrel Asnah Asnah Assyfa, Zahra Putri Astutik Astutik Asvinia, Made Astri Aulia, Tazkia Aulya, Sindi Azima, Muhammad Fauzan Bagus Prihadi Bengi, Chinta Simah Budiyono (SINTA ID : 6185108), Debora Budiyono, Debora Chiara, Novita Adya Damayanti, Irah Dani Rofianto Daniel , Daniel Daniel, Prima Audia Darjat Sudrajat, Darjat Darma Satria Davinsy, Rynaldi Deni Firmansyah Denny Andreas Denny Kurniawan Desi Ratna Sari, Desi Ratna Dewi, Deshinta Arrova Dian Indah Sari Dina Warsahanda Dona Yuliawati Edi Edi Pranyoto Egi Safitri Fachrul Razi Fahmi, Ali Fahriza, Ahmad Zulfa Fahruridho, Chicha Aprilia Fajri, Ika Nur Falahudin, Anisa Findia Farhaty, Mutiah Fatahillah, Dimas Fazhar Sumantri Ferdi, Muhammad Firman syah, Firman Fitria - Fitria Fitria Frisca Florensia Giannakos, Antonios Gustafito, Naufal Nuha Guswati, Jeni Vira Halimah Halimah Handoko, Melyani Harijanto Wijaya Hasibuan, Khoiriyah Azzahra Hasibuan, M.S. Hendra Kurniawan Hendra Lesmana Hermanto HERMANTO Herwanto, Riko Herwanto, Riko Hidayat Hidayat Hovivah, Hovivah Ihsan, Fathir Indah Sukma Wahyuni Irawan Setyabudi Irianto, Suhendro Y. Irmanelly, Irmanelly Irsyah, Abid Dhiyauddin Alfani Jamil, Pernando Aditya Jeki, Jeki johannes johannes Juliani, Duwi Jumanto Jumanto, Jumanto Kaban, Anggi Rona BR Kadafi, Kadafi Khairunisa, Titi Khalisa, Ighra Khoiruddin, Lukman Khoirunnisa, Dianis Januar Ko Ko Htet, Kyaw Kurniawan, Tri Basuki Lilik Joko Susanto Lina Karlinasari Luh Titi Handayani, Luh Titi M Yusendra M. Zaky Fanany Zaky Maensya, Alendra Natuah Maghfiroh, Miftahul mahdi mubarok Marbun, Elsa Agustin Maria, Okta Mariyam, Luayyi’ Dewi Marzuki, Farhan Masita, Masita Melda Agarina Melyani Melyani, Melyani MMSI Irfan ,S. Kom Mochammad Imron Awalludin Mohammad Muslich Muchsin, Gaisha HA. Muhamad Ariza Eka Yusendra Muhammad Ariza Eka Yusendra Muhammad Aulia Rahman Muhammad Fauzan Azima Muhammad Redintan Justin Muhammad Sahri Muji Lestari Mukhlis Mukhlis Muktiawan, Danang Ade Mu’awana, Saiti Nadhir, Ahnaf Ronaldo Nana Supriatna Nasution, Abdullah Habib Nasution, Nur Ati'ah Nauval, Iflan Neldawati, Rika Neni Purwati Nikentari, Nerfita Novi Herawadi Sudibyo Nujaima, Ismi Nurhayanto, Nurhayanto Nuri Cahyono Nurjoko Nurlistiani, Rini Nursiyanto Nurul fadillah, Nurul Oktaviani, Eva Oscar, Gusnanda Pakpahan, Lingghom Miranda Hanum Pangolangan Harahap, Cyndi Aulia Pasaribu, Gusti Aprila Pedliyansah, Yogi Permana, Sendy Pohan, Dedi Rusdi Pradana, Arya Pratama, Raynaldo Syah Pratama, Wanda Andika Putra, Iwan Eka Putra, Rizky Samjaya Putri, Amelia Putri, Lora Septrianda Raden Abdurrahman Rahayu, Yunie Rahayuningsih, Tri Yanti Rahmawati , Emilia Ramadhan, Riska Dwi Ramadhan, Rizki Aditya Ramadhani, Aisyah Revy, Ramzy Aranzha Riedanto, Muhammad Bayu Adithya Rifqatunnisak, Rifqatunnisak Rini Nurlistiani Rini Tri Astutik Ritha, Nola Rizal, Ruki Rizalnul Fikri, Ruki Rohiman Rohiman Rohiman Rohiman Romadona, Romadona Rosdiana, Yanti Rossa Wulandari Rovy Pratama, Rovy Ruki Rizal Sadri, Irsad Safitri, Egi Safitri, Rosi Mega Sahda, Dianita Saparudin Saparudin Saputra, M Hardi Saputra, Panggih Prabowo Rona Sasya Nadira Satrio, Rafli Banu Septiawan, Yuda Silalahi, Intan Aprillia Simbolon, Fidelis Simbolon, Lasro Dearma Br Siregar, Wahyu Andreansyah Siswoyo Siswoyo Sitompul, Ibnusyah So, Kristianto Wibison Solehudin, Didin Solly Aryza Sri Andika Putri Sri Karnila Sri Karnila Sri Karnila Sri Karnila Karnila Sri Lestari Sri Muryati Sri Rahayu Stefanus Rumangkit Stefanus Rumangkit Sudrajat, A. Suhada, Fizria Suherman, Suherman Sumarya, Edi Sumiati, Astri Suntono, Annita Rosliana Supriyadi Susanti Susanti Susanti Susanti Susanto, Lilik Joko Sushanty Saleh Susilawati , Esti Sutan Sahala Muda Marpaung Sutedi Sutedi Syabrinildi, Syabrinildi Syahrizal Syahrizal Syidada, Amran Rahman Telnoni, Sipora Petronela Theresia, Sumini Tri Erri Astoeti TRISTANTO ARI AJI Triyasri, Novita Uma, Syarfa Utami, Nesa Tri Valensia, Alda Caesar Via Lailatur rizki Viqri, Afril Wicakso Bandung Bondowoso Widijanto Sudhana Wijaya, Nanda Y, M Ariza Eka Y. Suhendro Yahya Muhaimin Yama, Tri Melda Yan Aditiya Pratama Yayuk Kusumawati Yoga Pristyanto Yogi Pedliyansah Yudiyanto, Muhammad Resa Arif Yuliana , Dwi Eva Yulifar, Leli Yuni Arkhiansyah Yusminar Yusminar Yusminar Yusminar Yusril, Muhamad Zahra Zahwa, Ananda Zulham Zulham