Evaluasi Kualitas Layanan Aplikasi Disney+ Hotstar Berdasarkan Analisis Sentimen pada Google Play

Abstract

Over-The-Top (OTT) is a content provider service that can easily accessed via the internet and streamed to compatible devices. With a rating of 3.4, Disney+ Hotstar is one of the OTT apps that are available on Google Play. Due to the fact that there are so many reviews on Google Play, sentiment analysis using text mining is required. Since competition among OTT services continues to grow, the Disney+ Hotstar service has to evaluate service quality in order to maximize their service quality. The purpose of this study is to assess the service quality of the Disney+ Hotstar application based on user sentiment and make recommendations for enhancing service quality. The research's primary data comes through observation and web scraping, while the secondary data came from literature studies. Pre processing, labeling, and classification with Support Vector Machine (SVM) are used in the sentiment analysis process. According to the research findings, sentiment analysis using the Support Vector Machine (SVM) algorithm has an extremely high accuracy of 88.46%. According to the negative sentiment, there are various quality issues, including not being able to properly use the service, application feature problems, payment system problems, response problems to user complaints, and problems regarding the aesthetic of the app. Suggestions for improvements involve frequent assessment and maintenance of server bandwidth, regular evaluation of content and adding additional features to apps, increasing integration with partner providers, improving customer service in responding to subscriber concerns, and evaluating and re-designing thesearch feature of the app.