PENERAPAN ALGORITMA C4.5 PADA ULASAN APLIKASI SHOPEE DI GOOGLE PLAY STORE - Indra Fitri Andriasih; Alexius Endy Budianto; Ainia Walidaroyani (Prodi Teknik Informatika, Fakultas Sains dan Teknologi, 2026)
Shopee, as one of the most popular e-commerce platforms in Indonesia, receives numerous user reviews on the Google Play Store. These reviews contain valuable information that can be leveraged to evaluate the quality of the application’s services. This study aims to classify user sentiment using the C4.5 algorithm to assist developers in better understanding user perceptions. The data were collected from the Google Play Store and processed through several stages, including preprocessing (case folding, stopword removal, stemming, word normalization, and sentiment labeling), data transformation using the TF-IDF method, and splitting the dataset into training and testing sets. The C4.5 algorithm was implemented using the DecisionTreeClassifier model with entropy as the criterion. The results indicate that the classification model achieved an accuracy of 83.25% on the test data. The model demonstrated strong performance in classifying positive sentiment, while the classification of negative and neutral sentiments was less optimal due to class imbalance. Therefore, the C4.5 algorithm proves to be effective in classifying user review sentiment, particularly in identifying positive sentiment. These findings can serve as valuable input for Shopee's developers to improve their services based on user feedback.