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All Journal UG Journal Justek : Jurnal Sains Dan Teknologi Journal on Education Jurnal Widya
Stevianus Stevianus
Universitas Gunadarma
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Mathematics Social Sciences

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Journal : Justek : Jurnal Sains Dan Teknologi

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MobilenetV2 Architecture To Detect Covid-19 X-Ray Imagery Widi Hastomo; Adhitio Satyo Bayangkari Karno; Ellya Sestri; Eva Karla; Stevianus Stevianus; Dodi Arif
Justek : Jurnal Sains dan Teknologi Vol 5, No 2 (2022): November
Publisher : Unversitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/justek.v5i2.11820

Abstract

Abstract:  The COVID-19 pandemic has hit all over the world, in the last two years and has changed the pace, structure and nature of social life. This study aims to detect COVID-19 using a chest x-ray image dataset sourced from kaggle.com, which is divided into 4 categories. The proposed method is CNN with MobileNetV2 architecture, by dividing 80% train data and 20% test data into 224x224 and batch size 32. The optimizer uses SGD, lr 0.005, momentum 0.9 and epoch 20. The results of the study with the achievement of precision values for the covid category 0.99, lung opacity 0.98, normal 0.96 and viral pneumonia category reached 0.99. Further studies can use the development of the CNN model and can try with other optimizers.Abstrak: Pandemi covid-19 telah melanda diseluruh dunia, dalam dua tahun terakhir dan mengubah langkah, struktur dan sifat kehidupan bermasyarakat. Penelitian ini  bertujuan untuk mendeteksi covid-19 menggunakan dataset citra chest x-ray yang bersumber dari kaggle.com, yang dibagi menjadi 4 kategori. Metode yang diusulkan yaitu CNN dengan arsitektur MobileNetV2, dengan membagi data train 80% dan data test 20% ukuran citra menjadi 224x224 dan batch size 32. Optimizer menggunakan SGD, lr 0.005, momentum 0.9 serta epoch 20. Hasil penelitian ini dengan capaian nilai presisi untuk kategori covid 0.99, lung opacity 0.98, normal 0.96 dan kategori viral pneumonia mencapai 0.99. Studi selanjutnya dapat menggunakan pengembangan dari model CNN serta dapat mencoba dengan optimizer yang lain.
Co-Authors Adhitio Satyo Bayangkari Karno Dodi Arif Ellya Sestri Eva Karla Muji Santoso Widi Hastomo