Analisis Sentimen Keluhan Layanan Cash on Delivery (COD) pada Platform Shopee Menggunakan IndoBERT - Musa Rahanra; Rooy marthen Thaniket; Nicodemus Rahanra; Hermanus J Suripatty (Jurnal IT UHB, 2026)
This study aims to analyze user review sentiment regarding the Cash on Delivery (COD) service on the Shopee e-commerce platform using the IndoBERT model. The dataset consisted of 1,840 unique Google Play Store reviews related to COD collected from September 25, 2018, to December 29, 2023. The stages of the research included data collection, text preprocessing, sentiment labeling, and modeling using IndoBERT. The results show that 48.4% of the reviews were negative, 41.1% positive, and 10.5% neutral. The IndoBERT model achieved an accuracy of 92.1%, with a weighted precision of 0.923, weighted recall of 0.921, and weighted F1-score of 0.922. The results indicate that the IndoBERT method is capable of classifying sentiments with good performance. The findings provide an overview of users’ perceptions of the COD service on Shopee. However, this study is limited to the use of a dataset from a single platform and cannot be generalized to all e-commerce platforms in Indonesia. Future research should use cross-platform datasets to obtain more comprehensive results.