Alfagift is a mobile application developed by Alfamart to support online ordering, with features such as promos, transactions, ordering, and delivery from the nearest point according to the consumer's address. User feedback on the Google Play Store shows mixed sentiments, including both positive and negative responses, which can be utilized by developers as material to improve the quality of the application. This study focuses on assessing the sentiment of Alfagift app user reviews through the application of the Random Forest algorithm. A total of 4,379 review data was collected from the Google Play Store and grouped into two categories, namely positive and negative sentiment. The research steps include data collection, data labeling, data preprocessing, word weighting, data division into training and testing sets, Random Forest algorithm implementation, and model evaluation. The test results show that the Random Forest algorithm achieves an accuracy of 97.6% and an AUC of 0.98, which falls into the category of excellent classification. This research is expected to contribute to application developers in understanding user perceptions, so as to improve application quality and increase overall user convenience.