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All Journal Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) Jurnal Buana Informatika Journal of Degraded and Mining Lands Management TRANSISTOR Elektro dan Informatika Jurnal Ilmu Ekonomi dan Pembangunan Warta Penelitian Perhubungan Economics and Finance in Indonesia Indonesian Journal of Community Services Wayang Nusantara: Journal of Puppetry Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Sosiohumaniora Kodepena (JSK) Community Empowerment International Journal of Business, Law, and Education East Asian Journal of Multidisciplinary Research (EAJMR) PELS (Procedia of Engineering and Life Science) ASMAT: Jurnal Pengabmas International Journal of Health Science (IJHS) Journal of Islamic Business Management Studies (JIBMS) Prosiding Seminar Riset Mahasiswa Indo-Fintech Intellectuals: Journal of Economics and Business Gema Kesehatan Jurnal Rekayasa Sistem Informasi dan Teknologi IIJSE Journal of Economics, Business, Accounting and Management Management Studies and Business Journal Jurnal Pengabdian Masyarakat Ekonomi dan Bisnis Digital IJETH Media Penelitian dan Pengembangan Kesehatan Edusight Jurnal Pengabdian Masyarakat (EduJPM) Journal of Sharia Economy and Islamic Tourism Warta Penelitian Perhubungan
Sri Mulyono
APIKES Mitra Husada Karanganyar
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Journal : Jurnal Buana Informatika

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Prediksi Penyakit Batu Ginjal dengan Menerapkan Convolutional Neural Network Waluyo Poetro, Bagus Satrio; Mulyono, Sri; Vani Aulia Pramesti
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Kidney stones are a health problem that requires intensive treatment. If the disease is not treated quickly, it can lead to impaired kidney function and complications to other organs. Computerized Tomography Scan (CT Scan) with high resolution is used to scan the human body for disease diagnosis. The doctor will explain the diagnosis within a few days or one week. This research aims to create a prediction model for the classification of kidney stone disease through CT Scan images by applying the Convolutional Neural Network (CNN) method of DenseNet-121 architecture and deployment using Streamlit. The results of the model in this study with the application of CNN DenseNet-121 architecture are accuracy 98.18%, precision 96.36%, recall 100%, and F1-score 98.14%.
Prediksi Penyakit Batu Ginjal dengan Menerapkan Convolutional Neural Network Waluyo Poetro, Bagus Satrio; Mulyono, Sri; Vani Aulia Pramesti
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Kidney stones are a health problem that requires intensive treatment. If the disease is not treated quickly, it can lead to impaired kidney function and complications to other organs. Computerized Tomography Scan (CT Scan) with high resolution is used to scan the human body for disease diagnosis. The doctor will explain the diagnosis within a few days or one week. This research aims to create a prediction model for the classification of kidney stone disease through CT Scan images by applying the Convolutional Neural Network (CNN) method of DenseNet-121 architecture and deployment using Streamlit. The results of the model in this study with the application of CNN DenseNet-121 architecture are accuracy 98.18%, precision 96.36%, recall 100%, and F1-score 98.14%.
Co-Authors A. Faroby Falatehan Abdillah, Minan Ade Onny Siagian Aghni Aulia Aziz Ahmad Jalaluddin, Ahmad Ainun Najib Albasri Aliman Aliman Andika, Ardhi Dwi Anwar Arif, Asrianti Aslan Aslan, Aslan Ayomi, Andreas C. Badie'ah, Badie'ah Badieah Assegaf Badie’ah, Badie’ah Baehaqi Bhimo Rizky Samudro, Bhimo Rizky Dedy Arisjulyanto Denpharanto Agung Krisprimandoyo Edward Kurniawan Saputra Letsoin Eva Desembrianita Faisal Danu Tuheteru Gholib, Tsabit Ghufron, G Habibi, Muhammad Syihab Haris, Ibnu Hermawan, Hildan Mulyo Hidayat, Ilham Himawan, Ade Husna Ika Purnama Sari Irawati, Intan Josua Panatap Soehaditama Jusman, Ikhsan Amar Kusuma, Ardhanari H. Mangkusuwondo, Suhadi Markus Mofu, Renald Marzuki . Mofu, Renold Muhammad Muhammad Aria Wahyudi Mukaromah, Naela Mulyani, Wiwiek Nelly Nur Anna Chalimah Sadyah Nuraprila, Shintia Pamungkas, Akbar Ilham Perwitasari, Erni Pratiwi Poetro, Bagus Satrio Waliyo Poetro, Bagus Satrio Waluyo Primadi Candra Susanto Putra, Purniadi Putra, Wira Pramana Putri, Nadira Awalia Rahmi Rahmi Riansyah, Andi Riziq, Alvin Yusuf Rozi, Muhammad Faris Fahru Sam Farisa Chaerul Haviana Saputra, Didin Hadi Satyagraha, Muhammad Thifan Soedomo, R. Pramono Soedomo, R. Pramono Sri Sugiarsi Suhardi, Muhamad Sulaiman, Noor Suhana Sulfarid, Sulfarid Sumardi . Sungkowati, Sri Suryani . Sutrisnon, Trismianto Asmo Syakhrani, H. Abdul Wahab Syamsuddin, Nurfiani Tarjono, Tarjono Trismianto Asmo Sutrisno Tuheteru, Edy Jamal Vani Aulia Pramesti Wiwin Rahmawati Nurdin Yacob, Azliza Yuliastuti, Hilda Zahrul Fuadi