A Review of Sentiment Analysis of Customer Reviews of Kopi Kenangan App: A Case Study on Customer Experience Improvement Approach

This study aims to conduct sentiment analysis on customer reviews on the Kopi Kenangan application as a case study in an effort to improve customer experience. Sentiment analysis is the process of extracting subjective information from text data to determine the polarity of sentiment, whether positive, negative, or neutral. In this study, we use a machine learning approach with an auto-model system to classify customer review sentiment. Customer review data is collected from various online sources and manually labeled for use as training data. We compare the performance of several classification models, such as Naive Bayes, Support Vector Machines (SVM), and Logistic Regression, and optimize the parameters to obtain the best results. The ranking of the best system classification will be analyzed and interpreted to provide insight into customer sentiment towards the Kopi Kenangan application. The results of this study can help management identify areas that need improvement and make strategic decisions to improve the overall customer experience.