DETEKSI CITRA DIGITAL PENYAKIT CACAR MONYET MENGGUNAKAN ALGORITMA CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR MOBILENETV2 - Putri Sarah Fransisca (2023)
In July 2022, monkeypox was declared a global health emergency due to its occurrence in more than 70 countries. The first case of monkeypox in Indonesia was discovered in Jakarta in August 2022. Differentiating between monkeypox, chickenpox, and measles, which share similar symptoms, poses a challenge for healthcare workers. To address this, a research study was conducted to develop an automated algorithm for detecting digital images of monkeypox. The algorithm used was a Convolutional Neural Network with MobileNetV2 architecture, implementing transfer learning. The model was trained for a total of 5 epochs and utilized two types of optimizers, namely Adam and RMSprop. Applying Adam Optimizer with a learning rate of 10-4 resulted in a test accuracy of 94%, training accuracy of 92%, and a loss function value of 27%. On the other hand, implementing RMSprop Optimizer with a learning rate of 45×10-3 achieved a test accuracy of 97%, training accuracy of 97%, but with a relatively higher loss function value of 52%.