Perancangan Model Pengenalan Citra Digital Tomografi Paru-Paru Untuk Deteksi Covid-19 Menggunakan Jaringan Saraf Tiruan
DOI:
https://doi.org/10.34818/eoe.v8i6.17039Abstract
Penyakit COVID-19 atau Coronavirus telah menjadi pandemi global dan menjadi masalah utama yang harus segera dikendalikan. Salah satu cara yang dapat dilakukan adalah memutus rantai penyebaran virus tersebut dengan melakukan deteksi dan melalukan karantina atau isolasi diri. Pencitraan digital dengan menggunakan pemindaian tomografi komputer (CT scan) dapat dijadikan alternatif dalam mempelajari COVID-19. Pencitraan digital dengan pemindaian tomografi komputer (CT scan) dianggap mampu menggambarkan kondisi paru-paru pada pasien terinfeksi COVID-19 dan dapat menjadi alat bantu diagnosa klinis. Pada penelitian ini, melakukan klasifikasi COVID-19 dengan mengenali gambar pada pemindaian tomografi komputer (CT scan) paru-paru dengan menggunakan teknik dalam pengolahan citra digital dan ekstraksi fitur GLCM dilanjutkan pembuatan model jaringan saraf tiruan sehingga citra CT scan paru-paru dapat diklasifikasi oleh model. Hasil pada penelitian ini mendapatkan model yang paling optimum untuk klasifikasi COVID-19 dengan performansi accuracy sebesar 93%, precision sebesar 90%, recall sebesar 96% dan F1-score sebesar 93%. Kata Kunci: COVID-19, pemindaian tomografi komputer (CT scan) paru-paru, pengolahan citra digital, jaringan saraf tiruanReferences
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