Analisis Sentimen Pengguna Aplikasi Taobao Berdasarkan Rating dan Ulasan di Google Play Store Menggunakan Algoritma K-Nearest Neighbor (KNN) - Andri Kurniawan; Muhammad Habiburahman; Muhammad Rezki Maulana (Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI), 2025)
This study aims to analyze the sentiment of Taobao application users on the Google Play Store using the K-Nearest Neighbor (KNN) algorithm. The methodology used includes the process of collecting data through web scraping from user reviews, then carrying out data preprocessing processes such as casefolding and tokenizing before being applied to the sentiment classification model. The results of the study indicate that the KNN algorithm is able to classify sentiment with an accuracy rate of around 62%, with most reviews being negative and the limited amount of data being a factor inhibiting model performance. These findings provide a basis for the development of better sentiment analysis models and can help application developers and e-commerce entrepreneurs understand user perceptions and improve the quality of their services. This study also suggests that more complex models and data sampling techniques can be used to obtain more accurate results in the future