Decision Support System for Sunscreen Selection Based on Facial Skin Concerns Using the Analytic Network Process

Abstract

Exposure to ultraviolet (UV) radiation is one of the primary causes of premature skin aging and various facial skin problems. However, selecting an appropriate sunscreen product remains challenging due to limited consumer knowledge and the overlapping nature of facial skin concerns. This study proposes a decision support model using the Analytic Network Process (ANP) to determine the most suitable sunscreen product based on six common skin problems: acne-prone skin, very dry skin, outdoor-induced dullness, aging, hyperpigmentation and acne scars, and general dullness. These criteria were derived from literature and validated by a certified skincare expert. Nine sunscreen alternatives from the Wardah brand—chosen due to their wide usage in the Indonesian market and varying SPF, PA levels, and formulations—were evaluated. Expert judgment was used in pairwise comparisons, with Consistency Ratio (CR) used to ensure reliability. The ANP model was developed using unweighted, weighted, and limit supermatrices. Results showed that Wardah UV Shield Aqua Fresh Sunscreen Serum SPF 50 PA++++ had the highest global priority score. A prototype web-based system was built using PHP and MySQL to deliver personalized sunscreen recommendations. The novelty of this study lies in its integration of expert dermatological insights and the use of ANP to address interrelated skin concerns, which are rarely explored in prior skincare decision support research.