Saputra, Muhammad Al Hakim and , Fatah Yasin Al Irsyadi, S.T., M.T. (2026) Rancang Bangun Aplikasi Mobile untuk Klasifikasi Penyakit Kulit Menggunakan Model Convolutional Neural Network (CNN) dengan Penerapan Teknik Augmentasi Data. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
Skin diseases are a common health issue in Indonesia, yet access to dermatologist diagnosis remains limited and costly, making AI powered mobile applications a potential solution for preliminary screening. This study aims to design and implement a mobile application for skin disease classification using a Convolutional Neural Network (CNN) algorithm, applying data augmentation and class weighting techniques to address class imbalance. The CNN model was converted to TensorFlow Lite format for optimal execution on the Android platform. System evaluation encompassed model performance measurement, Black Box testing, the System Usability Scale (SUS), and medical expert validation. The results showed that the CNN model achieved an overall accuracy of 91%, with relatively balanced precision, recall, and F1-score values across all classification classes. The usability evaluation involving 30 respondents yielded an average SUS score of 76.17, categorized as Good (Acceptable). Medical expert validation confirmed the application's feasibility as a non-diagnostic preliminary screening tool. This study demonstrates that data augmentation effectively improves medical image classification quality under limited data conditions, and the developed system supports users in identifying skin diseases independently.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Skin Disease, Image Classification, Convolutional Neural Network (CNN), Mobile Application, Data Augmentation |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software > QA761 Application Software R Medicine > Dermatology T Technology > Information Technology > Artificial Intelligence T Technology > Information Technology T Technology > Information Technology > Software. Aplication |
| Divisions: | Fakultas Komunikasi dan Informatika > S1 Teknik Informatika |
| Depositing User: | MUHAMMAD AL HAKIM SAPUTRA |
| Date Deposited: | 12 May 2026 04:46 |
| Last Modified: | 12 May 2026 04:46 |
| URI: | http://eprints.ums.ac.id/id/eprint/144904 |
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