ANALISIS CITRA ULTRASONOGRAFI BERBASIS AI UNTUK PENILAIAN PENUAAN KULIT AI-Based Ultrasound Image Analysis for Skin Aging Assessment

Razqiyah, Farah Putri (2025) ANALISIS CITRA ULTRASONOGRAFI BERBASIS AI UNTUK PENILAIAN PENUAAN KULIT AI-Based Ultrasound Image Analysis for Skin Aging Assessment. Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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Abstract

As humans age, their skin undergoes various structural changes, such as a loss of elasticity, increased wrinkling, and alterations in dermal thickness and echogenicity. High-Frequency Ultrasound (HFUS) technology is a non-invasive imaging method capable of providing detailed visualization of skin layers, making it highly promising for assessing the degree of skin aging. However, manual analysis of HFUS images is considered inefficient and time-consuming. Furthermore, dataset imbalance poses a challenge that can affect model classification performance. This study aims to develop and evaluate a classification model based on the Gradient Boosting Machine (GBM) algorithm to analyze HFUS images for skin aging assessment. The research was conducted in several stages: data preprocessing, labeling, feature extraction (using HOG, LBP, and GLCM), model training, and performance evaluation based on accuracy, precision, recall, and F1-score metrics. The dataset comprised 17,425 HFUS images of facial skin, obtained from 44 patients across four separate scanning sessions using the DUB SkinScanner75 device. The study resulted in an accurate and reliable classification model for analyzing skin aging conditions. This model is expected to enhance clinical diagnostic efficiency and serve as an artificial intelligence-based technological solution in modern dermatology. Keywords: Skin Aging, High-Frequency Ultrasound (HFUS), Artificial Intelligence (AI), Gradient Boosting Machine (GBM), Image Analysis

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Skin Aging, High-Frequency Ultrasound (HFUS), Artificial Intelligence (AI), Gradient Boosting Machine (GBM), Image Analysis
Subjects:	R Medicine > R Medicine (General) R Medicine > RZ Other systems of medicine
Divisions:	Fakultas Teknik > Program Studi Teknik Informatika
Depositing User:	1462100122 Farah Putri Razqiyah
Date Deposited:	23 Jun 2026 03:35
Last Modified:	25 Jun 2026 02:30
URI:	http://repository.untag-sby.ac.id/id/eprint/45807

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