Skin Disease Detection For Independent Treatment Based on Classification of Data

Arnandya, Muhammad Audino Fakhri (2023) Skin Disease Detection For Independent Treatment Based on Classification of Data. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

This research aims to develop a skin disease detection system through image processing using state-of-the-art technology. The system utilizes artificial intelligence (expert system) and image processing methods to identify types of skin diseases based on user-provided information. The output of the system includes the name of the disease, its impact, causes, and remedies. The system also includes an FAQ feature to assist users in manual disease detection. The scope of the system encompasses user registration, disease detection, image scanning, and a dictionary feature containing information on prevention, treatment, and suitable medications. The benefits of this research are the development of an Android-based application that can detect common skin diseases, provide non-prescription medication advice, and offer prevention information. The assumption of this research is that the system can facilitate the public in detecting skin diseases and serve as a valuable tool for managing expert knowledge on common skin diseases. The project constraints include focusing on symptom-based questions, providing initial references for common skin diseases, and requiring appropriate images for accurate scanning. The literature review emphasizes the importance of detecting and managing skin diseases, as well as the role of mobile applications, artificial intelligence systems, and Convolutional Neural Network (CNN) methods in skin disease detection. High-quality medical data sources such as the ISIC Archive and the Kaggle platform are also revealed as relevant sources for the development of a skin disease detection system.

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