Analisis Data Sentimen Ulasan Pengguna Aplikasi Shopee di Google Play Store dengan Klasifikasi Algoritma Naïve Bayes

Wartumi Wartumi (STMIK IKMI Cirebon)
Rudi Kurniawan (STMIK IKMI Cirebon)
Yudhistira Arie Wijaya (STMIK IKMI Cirebon)

Jurnal Informatika dan Rekayasa Perangkat Lunak
Vol 6, No 1 (2024): Maret

This research focuses on analyzing sentiment data from users of the Shopee e-commerce application using the Naïve Bayes Algorithm method. From 1000 datasets obtained from web scraping, reviews were analyzed to classify sentiment into positive or negative. With a ratio of 80% training data and 20% test data, the model developed achieved an accuracy of 95.5%. The classification results show precision 86.76%, recall 1%, and f1-score 92.91%. Even though the recall is low, the high accuracy shows that the model has good performance in predicting sentiment data. Recommendations can be provided to Shopee developers to improve customer satisfaction based on this sentiment data analysis.