The rapid adoption of e-wallet services in Indonesia has generated a large volume of user-generated reviews that provide valuable information about service quality, user satisfaction, and recurring technical problems. However, previous studies have commonly examined individual applications or emphasized classification performance, while cross-platform comparisons using a consistent Indonesian language model remain limited. This study conducts a comparative sentiment and exploratory complaint-term analysis of five widely used Indonesian e-wallet applications—DANA, OVO, GoPay, ShopeePay, and LinkAja—using IndoBERT. A total of 5,000 Google Play Store reviews were initially collected, of which 4,669 reviews remained after filtering and preprocessing. Ratings of 1–2 were used as negative proxy labels, whereas ratings of 4–5 were used as positive proxy labels, while three-star reviews were excluded. The dataset was divided into 80% training and 20% testing data using stratified sampling. The indobenchmark/indobert-base-p1 model was fine-tuned for three epochs using a learning rate of 2×10⁻⁵ and a batch size of 16. The best model achieved 84.36% accuracy and a positive-class F1-score of 73.45%. At the platform level, DANA recorded the highest proportion of positive reviews at 51.84%, whereas OVO showed the highest negative proportion at 84.77%. Exploratory complaint-term analysis identified recurring issues involving failed transactions, account balances, login and verification problems, application errors, and customer service. The findings demonstrate the usefulness of IndoBERT for analyzing Indonesian e-wallet reviews and provide a cross-platform perspective for identifying service improvement priorities in Indonesia's digital payment ecosystem.