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All Journal Jurnal Teknologi Dedikasi: Jurnal Pengabdian kepada Masyarakat Journal of Informatics and Information Security
Harini Agusta
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Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Education Electrical & Electronics Engineering Engineering Social Sciences Other

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Journal : Journal of Informatics and Information Security

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A Breakthrough in Viral Pneumonia Detection: Unveiling Insights with ResNet-152 Widi Hastomo; Adhitio Satyo Bayangkari Karno; Nani Kurniawati; Harini Agusta
Journal of Informatic and Information Security Vol. 4 No. 2 (2023): Desember 2023
Publisher : Program Studi Informatika, Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/1zcjsb83

Abstract

Viral pneumonia is one of the most serious health issues. The key problem in providing early detection and rapid mitigation through the use of chest X-ray imaging has become the ability to identify accurately. The ResNet-152 convolutional neural network approach will be used in this study to predict viral pneumonia. The input dataset was obtained from Kaggle.com. The accuracy findings from this investigation obtained a substantial value, namely 0.99, indicating that the model used performed admirably. The model used can efficiently distinguish between the viral pneumonia dataset and other datasets. It is intended that the findings of this study will be used to inform early decisions in related medical sectors.
Co-Authors Adhitio Satyo Bayangkari Karno Aji Digdoyo Anik Pebriana Anisah Anisah Artana, I Nyoman Donna Imelda Farhan Anggarkhsa Fauzhia Rahmasari Flora Elvistia Firdaus Fogot Endro Wibowo Ivan Kusuma Lubena Lubena Lubena, Lubena Muhammad Dzikri Akhira Nani Kurniawati Nurdina Widanti Rachmat Nursalam Rineta Visca Tri Surawan Widi Hastomo