Pengaruh Optimizer Terhadap Model Transfer LearningMobileNetV2 pada Klasifikasi Citra Penyakit Gigi dan Lidah

Dental and oral health is an integral part of overall body health that cannot be separated from general health. Issues such as tooth decay and periodontal disease have significant impacts on an individual's well-being and the population as a whole. Despite efforts to raise awareness of the importance of dental care, these health issues remain a major concern, especially in developing countries like Indonesia. Artificial intelligence technology, particularly Convolutional Neural Networks (CNNs), has offered promising solutions for automatically detecting and classifying dental and oral diseases. Some researchers have conducted studies in this field, but there are still shortcomings in terms of optimal models, limited data variations, and suboptimal accuracy levels. This research aims to address previous research limitations by utilizing a trained MobileNetV2 model and a more diverse dataset. Through this research, it is hoped to make a positive contribution to raising awareness and preventing dental and oral diseases