Published in Data Science and Engineering (DSE) Record 2025 Vol. 6 No. 1 pp. 184-193
Abstract
The healthcare sector is becoming more competitive, requiring businesses to understand consumer needs through sentiment analysis of feedback. This study analyzed feedback from Sriphat Medical Center to assess satisfaction (satisfied/dissatisfied) across eight as-pects, including service process, staff behavior, and medical expertise. Using Natural Lan-guage Processing (NLP) and machine learning with Bag-of-Words and the Term Frequency-Inverse Document Frequency (TF-IDF) techniques, the best-performing model was a linear SVM with 95.8% accuracy in satisfaction classification and 77.4% in aspect classification.