Penggunaan Aplikasi Big Data Analytics untuk Penyelesaian Masalah dan Analisis Performa Aplikasi berdasarkan Churn dan Retention Rate Pengguna pada Aplikasi Teman Bumil

This research aims to improve user experience to ensure an increase in user retention, which in turn reduces early user churn rate of the mobile application Teman Bumil using big data analytics. User data is analyzed to identify user churn patterns, understanding different factors that may affect it, and to devise a strategy that fits each user profile to improve user retention rate. In this research, user behavior is analyzed in-depth, which includes the understanding of when users become inactive and the events that lead to said decision. This data will help identify significant churn patterns and observe opportunities of customized solutions to remedy the problem. Research shows that 90% of Teman Bumil users became inactive app users during the first month. Data is then compared with competitors of equal footing, and from it, it can be assumed that distinctive features in Teman Bumil to promote uniqueness is still insufficient, thus indicating that Teman Bumil does not have a distinct set of features compared to its peers. Based on those findings, the solution offered to achieve said parity is to improve on the integration of current features to allow full utilization of the app’s features, especially to medical institutions, internal family circle, and other users. With these solutions, 41% increase in user retention is hoped and expected with the development and improvement of these childcentric features.