Analisis Sentimen Ulasan Aplikasi iPusnas di Playstore dengan Metode Algoritma Random Forest - Achmad Fauzi; Andi Dwi Pangestu; Ade Kurnia Solihin; Redo Abeputra Sihombing; Fauzan Natsir (Journal of Information Technology, 2026)
iPusnas is a digital library application developed by the National Library of Indonesia (Perpusnas RI) that allows users to borrow and read digital books via smartphones. As one of the most widely used digital library platforms in Indonesia, iPusnas has received thousands of user reviews on Google Play Store, reflecting various public sentiments about the application's performance and features. This study aims to analyze the sentiment of iPusnas user reviews on the Google Play Store using the Random Forest algorithm. Data were collected by scraping user reviews from the Play Store, followed by preprocessing steps including case folding, cleaning, normalization, tokenization, stopword removal, and stemming. Labeling was performed using the Lexicon-Based method. Feature extraction used TF-IDF (Term Frequency-Inverse Document Frequency), and data imbalance was addressed using the SMOTE (Synthetic Minority Over-sampling Technique) method. The results of the analysis showed that the Random Forest model achieved an accuracy of 73,60%, precision of 72,60%, recall of 72,10%, and F1-score of 72,30%, demonstrating its effectiveness in classifying positive and negative sentiments of iPusnas users.