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Tinaliah, Tinaliah
Universitas Multi Data Palembang
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Journal : Algoritme Jurnal Mahasiswa Teknik Informatika

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Klasifikasi Penyakit Cacar Menggunakan Arsitektur AlexNet Susanto, Rafael Ivan; Tinaliah, Tinaliah
Jurnal Algoritme Vol 5 No 1 (2024): Oktober 2024 || Algoritme Jurnal Mahasiswa Teknik Informatika
Publisher : Program Studi Teknik Informatika Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/algoritme.v5i1.9045

Abstract

Smallpox is a human skin disease that causes fluid-filled lumps, especially on the face and can spread throughout the body. There are several types of smallpox, including chickenpox (caused by the Varicella-Zoster virus), monkeypox (by the monkeypox virus), and cowpox (by the cowpox virus). Although smallpox is often considered mild, it can cause serious complications, especially for people with weakened immune systems. This research aims to develop an application that uses the Convolutional Neural Network (CNN) algorithm with the AlexNet architecture to help doctors diagnose types of smallpox. CNNs work similarly to the way the human brain recognizes objects in images. The dataset used consists of 3200 images 800 images for each type of smallpox and healthy skim, with 80% for training data and 20% for test data. The test results show the highest accuracy of 92%, using Batch size 16, Learning rate 0.0001, Optimizer Adam, and Epoch 40.
Co-Authors Abdul Rahman Amri Amri Andreas Danny Agus Wahyudi Bautista, Christian Chandra Saputra Cyndi Monica Deky Berniawan Derry Alamsyah Dicky Pratama Dicky Pratama gasim, Gasim Hafiz Irsyad Inayatullah Inayatullah Inayatullah, Inayatullah Johannes Petrus Lucretia, Jolyn Molavi Arman Niko Pirnando, Hendra Nata Novan Wijaya Pratama, Samuel Effendi Putri, Agnes Anastasia Putri, Anisah Dhiyaa Azzahra Susanto, Rafael Ivan Triana Elizabeth, Triana Wahyu Mustika Anggara Wilcent Yoannita Yoannita, Yoannita