ANALISIS SENTIMEN ULASAN SHOPEE DI PLAY STORE DENGAN NAIVE BAYES: Sentiment Analysis of Shopee Reviews on the Play Store Using Naive Bayes

Muh Arfah Wahlil Pratama (universitas muhammadiyah kolaka utara)
Suriyadi Suriyadi (Universitas Muhammadiyah Kolaka Utara)
Nurjaya Nurjaya (Universitas Muhammadiyah Kolaka Utara)
Haldi Alfaisal (universitas muhammadiyah kolaka utara)
Melni Melni (universitas muhammadiyah kolaka utara)
Andi Nurwafia (universitas muhammadiyah kolaka utara)
Nurkhafitri Sahra (universitas muhammadiyah kolaka utara)
Asya Syara Marzan (universitas muhammadiyah kolaka utara)
Arman Rusdin (universitas muhammadiyah kolaka utara)
Dirgasari Dirgasari (universitas muhammadiyah kolaka utara)

Jurnal Komputer dan Teknologi (JUKOMTEK)
Vol 5 No 2 (2026): JUKOMTEK JULI 2026

This study evaluates user sentiments towards the Shopee application on the Google Play Store using a dataset of 1,000 crawled reviews. Preprocessing methods including cleaning, normalization, stopword filtering, and stemming were conducted, followed by feature weighting using TF-IDF. The classification model based on the Naive Bayes Classifier yielded an overall accuracy of 84.5%, with a precision of 85.2%, recall of 83.8%, and F1-score of 84.5%. The analysis suggests that shipping promotions are the main drivers of positive sentiment, while post-update app performance drops and payment errors trigger negative reviews.