Klasifikasi Pengalaman Pengguna pada Platform Digital Menggunakan Algoritma Random Forest - Andin Sabilla Janna; M. Syaikh Azka; Zakirah Sabrina Putri Pasha; M. Putra Willy Nailis; Allsela Meiriza; Ken Ditha Tania; Ahmad Rifai (Universitas Merdeka Malang, 2026)
User experience on digital platforms was an important factor in determining service quality and platform success. This study classified user experience orientation based on User Interface (UI) and User Experience (UX) attributes using the Random Forest algorithm. The dataset was obtained from the Mendeley Data repository and contained 2,271 user evaluation records related to visual and functional elements across various digital platforms. The research stages included data normalization, label generation based on composite visual and functional scores, and model evaluation using 10-fold cross-validation. The results showed that Random Forest classified user experience orientation accurately and consistently, with an accuracy of 86.79%. Feature importance analysis indicated that Visual Hierarchy, Images and Multimedia, and Layout were the most influential attributes. These findings demonstrated that Random Forest was effective for analyzing user experience data and supporting digital platform improvement.