NLP-Based Sentiment Analysis of Alfagift and Klik Indomaret Application Reviews: A Comparative Study

Amid competition for online shopping applications, Alfagift and Klik Indomaret compete for the same market share. This study aims to analyze and compare user reviews of both applications using sentiment analysis based on Natural Language Processing (NLP) with the E-Servqual approach, focusing on Efficiency and System Availability indicators, to determine the advantages and disadvantages of each application and provide a basis for service improvement, strategic decision making, and reference for users in choosing online shopping applications that suit their needs. Methods include data collection, data grouping, data processing, selecting analyzed samples with consensus, and data analysis to describe user perceptions of the quality of service of each application. The results showed that on the positive side, both apps experienced an increase in efficiency although not significant, with gradual improvements in user experience. Alfagift showed improvements in technical responsiveness and ease of use, while Klik Indomaret was relatively stable with a simple user experience. On the negative side, efficiency issues still arise consistently and impact user perception. Alfagift often faces access and login issues, while Klik Indomaret tends to be slow when accessing various features. These findings reflect that despite year-on-year improvements, both apps still face technical challenges that need to be resolved to improve the overall quality of digital services.