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All Journal Jurnal Masyarakat Informatika Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURIKOM (Jurnal Riset Komputer) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi INTERACTION: Jurnal Pendidikan Bahasa Jurnal Teknologi Informasi dan Terapan (J-TIT) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Layanan Masyarakat (Journal of Public Service) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Advance Sustainable Science, Engineering and Technology (ASSET) Jurnal Mahasiswa Ilmu Komputer JAMU : Jurnal Abdi Masyarakat UMUS SmartComp Seminar Nasional Teknologi dan Multidisiplin Ilmu Jurnal Informatika: Jurnal Pengembangan IT Jurnal Sains dan Teknologi Informasi Jurnal Ilmu Komputer, Teknologi Dan Informasi SWAGATI: Journal of Community Service Masyarakat Berkarya: Jurnal Pengabdian dan Perubahan Sosial JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Muhammad Naufal
Dian Nuswantoro University, Semarang
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Enhancing Brain Tumor Classification on Mildly Imbalanced Datasets Using Categorical Focal Cross-Entropy Muhammad Naufal; Harun Al Azies; Farrikh Alzami; Novita Kurnia Ningrum; Rivaldo Mersis Brilianto; Pratidina Kusuma Dewi
Jurnal Masyarakat Informatika Vol 17, No 2 (2026): November 2026 (Ongoing Issue)
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.17.2.82619

Abstract

Brain tumor is a dangerous disease that requires accurate diagnosis, but medical datasets often suffer from class imbalance, resulting in bias in deep learning-based classification models. This study proposes using Categorical Focal Cross Entropy (CFCE) in a Convolutional Neural Network (CNN) to address this issue by comparing it with Categorical Cross-Entropy (CCE). CFCE is designed to emphasize minority class samples and hard-to-classify examples, thereby reducing the dominance of the majority class. Experiments were conducted on a brain tumor dataset with class imbalance, where the CNN model with CFCE achieved 84.57% accuracy, 83.57% precision, 85.27% recall, and 83.97% F1-score, outperforming the model with CCE (81.30% accuracy, 81.77% precision, 82.83% recall, and 81.15% F1-score). These results show that Focal Loss effectively improves the classification performance on imbalanced data, with a better ability to detect brain tumors, especially in the minority class. This study contributes to developing a more robust and reliable deep learning-based diagnosis system for medical applications.
Co-Authors Achmad Achmad Al Fahreza, Muhammad Daffa Al zami, Farrikh Al-Azies, Harun Alzami, Farrikh Amanda Cahyadewi, Felicia Amelia Safrida Amiq Fahmi Amron Amron Andrean, Muhammad Niko Anggi Pramunendar, Ricardus Anggita, Ivan Maulana Ardytha Luthfiarta ARIYANTO, MUHAMMAD Arofi, Muhammad Labib Zaenal Ashari, Ayu Ayu Pertiwi Azizi, Husin Fadhil Brilianto, Rivaldo Mersis Dairoh Dairoh Danar Cahyo Prakoso Dega Surono Wibowo Denta Saputra, Fahrizal Dewi Agustini Santoso Dewi Agustini Santoso Dewi Pergiwati Dewi Pergiwati Donny Amanullah Putra Rahman Dwi Puji Prabowo Edy Mulyanto Eko Purnomo Bayu Aji Erika Devi Udayanti Erwin Yudi Hidayat Esadhipa Raif Syihabuddin Fadlullah, Rizal Fahmi Amiq Farrikh Al Zami Farrikh Alzami Farrikh Alzami Farrikh Alzami Firmansyah, Gustian Angga Galih Putra Pratama Gilang Faturrahman Go, Agnestia Agustine Djoenaidi Guruh Fajar Shidik Gustina Alfa Trisnapradika Hadi, Heru Pramono Handayani, Ni Made Kirei Kharisma Harisa, Ardiawan Bagus Hartono, Andhika Rhaifahrizal Harun Al Azies Harun Al Azies Harun Al Azies Harun Al Azies Heni Indrayani Hepatika Zidny Ilmadina Hidayat, Novianto Nur Husin Fadhil Azizi Ibnu Richo Kurniawan Ifan Rizqa Indra Gamayanto Indrawan, Michael Iswahyudi ISWAHYUDI ISWAHYUDI Kharisma, Ni Made Kirei Khoirunnisa, Emila Kurniawan Aji Saputra Kurniawan, Defri Kusumawati, Yupie Levi Renov Esprayenduo Liya Umaroh Liya Umaroh Liya Umaroh, Liya Marcelinus Yosep Teguh Sulistyono Maulana, Isa Iant Megantara, Rama Aria Moch Anjas Aprihartha Moch Arief Soeleman, Moch Arief Mohammad Arif Mohammad Arif Muh. Fatkhi Alexander Muhamad Akrom Mukaromah Mukaromah MUKAROMAH MUKAROMAH Muljono, - Muslih Muslih Nazella, Desvita Dian Ningrum, Novita Kurnia Noor Ageng Setiyanto, Noor Ageng Novianto Nur Hidayat Novianto Nur Hidayat Novita Kurnia Ningrum Novita Kurnia Ningrum Nugraini, Siti Hadiati Nurayuni Kirana Muti Nurul Hashimah Ahmad Hassain Malim Paramita, Cinantya Prabowo, Wahyu Aji Eko Prasetya, Ibnu Pratidina Kusuma Dewi Puspita, Rahayuning Febriyanti Putra, Permana Langgeng Wicaksono Ellwid Rafi Jonathan Siger Rafid, Muhammad Rama Aria Megantara Rama Aria Megantara Ramadhan Rakhmat Sani Riadi, Muhammad Fatah Abiyyu Ricardus Anggi Pramunendar Ricardus Anggi Pramunendar Richard Christoper Subianto Richo Kurniawan, Ibnu Rivaldo Mersis Brilianto Rivaldo Mersis Brilianto Rivaldo Mersis Brilianto Ruri Suko Basuki Safitri, Aprilyani Nur Sindhu Rakasiwi Sofiani, Hilda Ayu Sri Winarno Sri Winarno Sudibyo, Usman Suharnawi Suharnawi SUPRIADI RUSTAD Tira Karel Agata Trisnapradika, Gustina Alfa Umar Fakhrizal, Irsyad Very Kurnia Bakti, Very Kurnia Virgiafan Rido Taufik Adrian Wahyu Aji Eko Prabowo Widyatmoko Karis Zahro, Azzula Cerliana Zami, Farrikh Al