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All Journal Jurnal Pendidikan dan Pembelajaran Khatulistiwa (JPPK) JAAKFE UNTAN ( (Jurnal Audit Dan Akuntansi Fakultas Ekonomi Universitas Tanjungpura) Indonesian Journal of Agricultural Research Jurnal Ilmiah Mandala Education (JIME) JUPE : Jurnal Pendidikan Mandala Kumawula: Jurnal Pengabdian Kepada Masyarakat JPDI (Jurnal Pendidikan Dasar Indonesia) ZAHRA: Research and Tought Elementary School of Islam Journal Sehat Masada NUCLEUS: Jurnal Sains dan Teknologi Forum Bisnis dan Kewirausahaan International Journal of Engagement and Empowerment (IJE2) Afeksi: Jurnal Penelitian dan Evaluasi Pendidikan Sosietas: Jurnal Pendidikan Sosiologi Algoritme Jurnal Mahasiswa Teknik Informatika Kronologi Jurnal Ilmu Pendidikan dan Kearifan Lokal (JIPKL) Jurnal Pengabdian Kreativitas Pendidikan Mahakam (JPKPM) JOURMICS : Journal of Media and Communication Studies Tensile : Jurnal Pengabdian Kepada Masyarakat TOFEDU: The Future of Education Journal Journal of Education, Religious, and Instructions (JoERI) Jurnal Pelita: Jurnal Pembelajaran IPA Terpadu Journal of Business Education and Social Journal of Citizen Research and Development
Sonia Sonia, Sonia
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Journal : Algoritme Jurnal Mahasiswa Teknik Informatika

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Penerapan Model U-Net untuk Segmentasi Gigi pada Citra Radiografi Panoramik Orang Dewasa Sonia, Sonia; Yohannes, Yohannes
Jurnal Algoritme Vol 5 No 2 (2025): April 2025 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i2.10965

Abstract

Dental and oral health play a crucial role in maintaining overall bodily health. Panoramic radiography serves as a primary diagnostic tool for analyzing dental and oral conditions; however, the complexity of its images often complicates manual analysis. This study aims to implement a Convolutional Neural Network (CNN) architecture for segmenting panoramic radiographic images, utilizing U-Net as the chosen model. The dataset used consists of panoramic radiographic images. The test results indicate that the implemented model achieved an IoU score of 0.8335 and a dice coefficient of 0.9092, demonstrating strong segmentation capability. These findings suggest that the proposed method can serve as a supportive tool for diagnosis and treatment planning in dental and oral healthcare.
Co-Authors Adriliana, Zairaini Aisya, Syifa Ayu Alfianti Alfianti Amran Thamrin Anastasia Sri Mendari Anggia Puteri Anggraini, Susiana Anwar, Hendra Azis, Irfani Basith, Abd. Christan, L.M Hari Dertha Mukhtar Dharmatanna, Sandjaja Emi Lestari Fadillah, Euis Fahru Raji Fransiska Soejono Gisella, Lea Gul, Hina Hakimah, Sayyidah Hamidah . Hudaifah, Hilda Idzni, Nurul Indra Lasmana Tarigan Indrianto, Iin Komang Sutawan Kusdar, Kusdar Linda Wati Lumbantoruan, Ester Martupa M. Sabiqul Huda Marzoan, Lalu Minangkabau, Siti Mawaddah Muhammad Ikhwan Muhammad Sahid Muhammad Zusanri Batubara Muhelni, Leila Muhsin Muhsin Munir Khan, Munir Mursalim Mursalim Natania, Winda Nopiana, Rizka Nur Agus Salim, Nur Agus Nyanabhadra, Phap Tu Padliawan, Muhamad Putri, Alya Adiningtyas Putri, Lioni Amelianti Rona, Rona Roziq, Toriq Sadozai, Khuram Nawaz Sardianto Sardianto, Sardianto Serliana, Serliana Silalahi, Lusia Desy Septiyana Sitepu, Agita Siti Mufarochah Sugeng, Santoso sukriadi sukriadi Sulistyarini, Sulistyarini Suprapto, Wasis Tri Nurhayati Asih Triana Indrayani Tuti Alawiyah Vinice, Melvyn Wahyuni, Irfina Wani, Wani Wati, Huda Marlina Wiranti, Ajeng Ratna Wiwik Handayani