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dc.contributor.advisorHarumy, T Henny Febriana
dc.contributor.advisorHandrizal
dc.contributor.authorSimanjuntak, Alex Mario
dc.date.accessioned2025-01-16T07:13:11Z
dc.date.available2025-01-16T07:13:11Z
dc.date.issued2024
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/100233
dc.description.abstractSkin diseases are a common health problem experienced by people in Indonesia, especially in areas with limited access to medical services. Early detection of skin diseases is very important, but it is often difficult to do without the help of medical professionals. Therefore, this research aims to develop an artificial intelligence-based diagnosis system that can help detect skin diseases more accurately. Convolutional Neural Network (CNN) has been proven effective in image classification and is implemented in this research. This research presents a solution for early diagnosis of skin diseases by utilizing CNN based on EfficientNetB7 for classification and YOLOv8 for detection. The system is designed to classify five types of skin diseases: Melanoma, Basal Cell Carcinoma (BCC), Melanocytic Nevi (NV), Benign Keratosis-like Lesions (BKL), and Seborrheic Keratoses and other Benign Tumors, and detect whether the disease is cancer or not. The results showed that the EfficientNetB7 model achieved 94% accuracy on the test data, while YOLOv8 showed detection performance with a mean average precision (mAP) of 0.812. The web-based system developed was able to process skin images and provide classification and detection results efficiently, and proved stable in various performance tests. The combination of EfficientNetB7 and YOLOv8 in the early diagnosis system of skin diseases has led to the development of a new system.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectConvolutional neural networks (CNN)en_US
dc.subjectEfficientNetB7en_US
dc.subjectYOLOv8en_US
dc.subjectSkin Diseaseen_US
dc.titleKlasifikasi dan Deteksi Penyakit Kulit Menggunakan Metode EfficientNetB7 dan YOLOv8 Berbasis Websiteen_US
dc.title.alternativeClassification and Detection of Skin Diseases Using Website-Based EfficientNetB7 and YOLOv8 Methodsen_US
dc.typeThesisen_US
dc.identifier.nimNIM201401034
dc.identifier.nidnNIDN0119028802
dc.identifier.nidnNIDN0113067703
dc.identifier.kodeprodiKODEPRODI55201#Ilmu Komputer
dc.description.pages98 Pagesen_US
dc.description.typeSkripsi Sarjanaen_US
dc.subject.sdgsSDGs 3. Good Health And Well Beingen_US


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