dc.contributor.advisor | Purnamasari, Fanindia | |
dc.contributor.advisor | Hizriadi, Ainul | |
dc.contributor.author | Saryandra, Vania Putri | |
dc.date.accessioned | 2024-08-30T08:49:09Z | |
dc.date.available | 2024-08-30T08:49:09Z | |
dc.date.issued | 2024 | |
dc.identifier.uri | https://repositori.usu.ac.id/handle/123456789/96456 | |
dc.description.abstract | Identifying facial skin type is an important aspect in dermatology and the cosmetics industry because each skin type requires different care. By knowing your skin type, more appropriate products and treatments can be recommended, thereby improving your skin's health and appearance. In this study, three types of facial skin were identified, namely normal skin, oily skin and dry skin. The data used in this research was processed using the SSD-MobileNet algorithm to detect and classify facial skin types. The research results show that the SSD-MobileNet algorithm is able to identify skin types with high accuracy. The overall average accuracy for the three skin types was 92.7%. These results show that the SSD-MobileNet algorithm is reliable in identifying facial skin types, which can be applied in various applications such as skin care and cosmetics. With high accuracy, this algorithm can help skin experts and the cosmetics industry provide more precise and efficient recommendations, as well as improve user experience in choosing appropriate skin care products. | en_US |
dc.language.iso | id | en_US |
dc.publisher | Universitas Sumatera Utara | en_US |
dc.subject | Facial skin identification | en_US |
dc.subject | SSD-MobileNet | en_US |
dc.subject | detection algorithm | en_US |
dc.subject | accuracy | en_US |
dc.subject | SDGs | en_US |
dc.title | Klasifikasi Jenis Kulit Wajah Dengan Menggunakan Algoritma SSD-MobileNet | en_US |
dc.title.alternative | Clasification Facial Skin Type Using SSD-MobileNet Algorithm | en_US |
dc.type | Thesis | en_US |
dc.identifier.nim | NIM171402080 | |
dc.identifier.nidn | NIDN0017088907 | |
dc.identifier.nidn | NIDN0127108502 | |
dc.identifier.kodeprodi | KODEPRODI59201#Teknologi Informasi | |
dc.description.pages | 66 Pages | en_US |
dc.description.type | Skripsi Sarjana | en_US |