Sentiment Analysis of Pinterest Application User Reviews Using ANN, CNN, and RNN Methods

The changes occurring in the pinterest application have sparked numerous opinions expressed on google playstore, both positive and negative. The purpose of this study is to analyze the sentiment of Indonesian public towards the Pinterest application through user reviews on the platform. The research method employed in this study is qualitative, utilizing data collection techniques through scraping user reviews and interviews. The research was conducted from October 2024 to January 2025. The data used consists of 2000 reviews collected in the years 2023 and 2024. This research uses 3 deep learning methods because they can understand large amounts of data. Others prefer machine learning as their research method because it is easier and less complicated. The RNN method is an effective method for performing sentiment analysis with large amounts of data. This is supported by research results indicating that the RNN (Recurrent Neural Networks) method achieved the highest accuracy in sentiment analysis, reaching 65.17%, followed by two other deep learning methods, namely CNN (Convolutional Neural Networks) and ANN (Artificial Neural Networks). The RNN method is effective because it is supported by high precision and recall values. The author suggests that future research should explore other methods and expand data from different platforms to gain a broader perspective.