<![CDATA[Investment is one of the most effective ways to achieve long-term financial gains. Nowadays, numerous digital platforms offer investment services, including the Ajaib application. The growing public interest in investing has been driven by influencers and online advertisements, yet it has also led to the rise of fraudulent schemes and fake investment platforms. Therefore, evaluating user satisfaction through sentiment analysis of application reviews becomes essential. This study aims to analyze user sentiments toward the Ajaib investment application based on reviews collected from the Google Play Store. The dataset consists of Indonesian-language reviews from the period 2019–2024, processed using Google Colab and the BERT (Bidirectional Encoder Representations from Transformers) algorithm. The classification results yielded 1,393 reviews, comprising 696 positive and 697 negative sentiments, indicating that negative opinions were slightly more dominant. The model achieved an accuracy of 85%, F1-score of 85%, recall of 85%, and precision of 87%, demonstrating that the BERT algorithm performs effectively in sentiment analysis for investment-related applications.]]>
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