Klasifikasi COVID-19 Menggunakan Algoritma CNN

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Muhammad Nuchfi Fadlurrahman
Agus Eko Minarno
Yufis Azhar

Abstract

X-Ray atau Sinar X merupakan teknik pencitraan pada bidang medis yang digunakan untuk melihat berbagai macam benda di dalam tubuh manusia yang tidak dapat dilihat langsung oleh mata manusia. Salah satu kegunaannya adalah melihat paru-paru manusia khususnya dalam mendeteksi COVID-19. Namun, Sinar X tidak dapat menembus tulang. Adapun salah satu metode klasifikasi citra adalah Convolutional Neural Network (CNN). CNN menerima input berupa gambar, menentukan aspek atau obyek apa saja dalam sebuah gambar yang bisa digunakan untuk mengenali gambar, dan membedakan antara satu gambar dengan gambar lainnya. Penelitian sebelumnya pada kasus ini menggunakan model CNN dengan arsitektur VGG-16. Penelitian ini bertujuan untuk membandingkan hasil akurasi akhir yang diperoleh model CNN dalam mengolah dataset Sinar X. Penelitian ini menggunakan CNN dengan arsitektur VGG-16 dan augmentasi data untuk mendapatkan akurasi yang tinggi. Berdasarkan hasil pengujian yang telah dilakukan menggunakan CNN dengan arsitektur VGG-16 dengan dataset sebanyak 3.829 data yang dibagi menjadidata train, validation, dan test dengan rasio split 80%, 10%, 10% penelitian ini mendapatkan hasil yang cukup baik dengan tingkat akurasi 90%.

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How to Cite
[1]
M. N. Fadlurrahman, A. E. Minarno, and Y. Azhar, “Klasifikasi COVID-19 Menggunakan Algoritma CNN”, JR, vol. 5, no. 2, Jan. 2024.
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