Husein, Muhammad Maulana and , Dedi Gunawan, S.T., M.Sc, Ph.D (2024) Sistem Klasifikasi Penyakit Kulit pada Manusia Menggunakan Machine Learning Berbasis Android. Skripsi thesis, Universitas Muhammadiyah Surakarta.
![[img]](https://eprints.ums.ac.id/style/images/fileicons/application_pdf.png) |
PDF (Naskah Publikasi)
Eprint_Skripsi_Muhammad Maulana Husein_l200200266.pdf Download (1MB) |
|
PDF (Surat Pernyataan Publikasi)
Surat Pernyataan Publikasi atau Tidak Publikasi_L200200266_mmhusein.pdf Restricted to Repository staff only Download (211kB) | Request a copy |
Abstract
Skin diseases are a common problem experienced by many individuals in Indonesia and can have a significant impact on their health and quality of life. Factors such as lack of attention to hygiene, exposure to harmful substances in the environment, infections, weather in tropical areas, and immune responses such as allergies and bacterial infections can trigger the emergence of various types of skin diseases. In the context of the challenge of early detection of skin diseases, this research aims to develop an Android-based application using a machine learning model with a Convolutional Neural Network (CNN) algorithm to classify types of skin diseases. The research results show that the application has been successfully developed and is able to detect 9 classes of skin diseases with a testing accuracy of 83.2%. This application not only provides information regarding types of skin diseases, but also relevant treatment guides. Black-box testing shows that the system functions well, and the System Usability Scale (SUS) assessment produces a score of 77.17, indicating the application is acceptable and suitable for use by users. Thus, this application can help people detect and understand skin diseases early on.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | android, CNN, machine learning, penyakit kulit, waterfall |
| Subjects: | T Technology > TZ Technical Information T Technology > TZ Technical Information > TA02 Software. Aplication > Pemograman |
| Divisions: | Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika |
| Depositing User: | MUHAMMAD MAULANA HUSEIN |
| Date Deposited: | 01 Aug 2024 07:38 |
| Last Modified: | 01 Aug 2024 07:38 |
| URI: | http://eprints.ums.ac.id/id/eprint/125758 |
Actions (login required)
 |
View Item |
