Klasifikasi Citra X-Ray Covid-19 Menggunakan Three-layered CNN Model
DOI:
https://doi.org/10.31358/techne.v21i2.316Keywords:
CNN, COVID-19, klasifikasi, deep neural network, X-rayAbstract
Tragedi Covid yang melanda dunia perlu mendapat solusi pendeteksian yang cepat untuk mempermudah pengobatannya. Metode tes PCR jumlah alatnya lebih sedikit dibandingkan dengan mesin X-ray di Indonesia. Oleh karena itu, metode pengklasifikasi gambar X-ray dapat digunakan sebagai solusi alternatif. Pada penelitian ini diusulkan penggunaan model CNN dengan tiga lapisan convolutional dan maxpooling. Dataset image yang digunakan memiliki 1000 image teridentifikasi Covid dan 3000 image sebagai normal. Hyperparameter tuning dilakukan dengan cara membandingkan beberapa kombinasi hyperparameter; learning rate, dropout rate dan density. Model terbaik yang didapatkan adalah model tiga lapisan neural network dengan learning rate = 0,001, density = 64 dan dropout rate = 0,7. Model ini memiliki rata-rata akurasi sebesar 96% dan jumlah parameter sebanyak 7,1% dibandingkan acuan.
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Copyright (c) 2022 Aaron Berliano Handoko, Ivanna Kristianti Timotius, Darmawan Utomo
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