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All Journal Jurnal Rekayasa Sistem Industri PRISMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING Conference on Innovation and Application of Science and Technology (CIASTECH) M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jusikom: Jurnal Sistem Informasi Ilmu Komputer
Kusumaningrum, Dwi Sulistya
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Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Journal : JOURNAL OF APPLIED INFORMATICS AND COMPUTING

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Application of Convolutional Neural Network (CNN) Algorithm with ResNet-101 Architecture for Monkey Pox Detection in Human Al Fathir Rizal Januar; Indra, Jamaludin; Kusumaningrum, Dwi Sulistya; Faisal, Sutan
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9621

Abstract

Monkeypox is a zoonotic disease that has spread to various countries, including Indonesia. It is transmitted through direct contact with skin lesions, respiratory droplets, or contaminated objects. Early and accurate detection is crucial to reduce the risk of transmission and improve treatment effectiveness. This study aims to detect monkeypox using a Convolutional Neural Network (CNN) with the ResNet-101 architecture. The pre-processing steps include normalization and resizing of images to 224×224 pixels. The model is trained using the Adam optimizer, categorical crossentropy loss function, and an adaptive learning rate reduction. Evaluation results show that the model achieved an accuracy of 94%, with a precision of 0.92, recall of 0.92, and an F1-score of 0.92. The model is capable of classifying images effectively, although some misclassifications still occur. This system is intended to function as an initial image-based screening tool, but its results should be confirmed through clinical diagnosis and laboratory testing to ensure accuracy.
Co-Authors Al Fathir Rizal Januar Faisal, Sultan Faisal, Sutan Fauzi Ahmad Muda Hakim, Mirwan Abdurrahman Indra, Jamaludin Jamal, Malikil Lestari, Santi Arum Puspita Nurapriani, Fitria Ridwan Maulana, Ridwan Rohana, Tatang