Service Quality Analysis of Mhealth Services Using Text Mining Method : Alodokter and Halodoc

Abstract

The digital transformation of health services causes an increasing number of digital health service providers in Indonesia. The user shares their experiences and reviews each other on the online platform. This study aims to understand user perceptions of m-health services in Indonesia based on m-health service quality with a big data approach. Research using text mining is derived from the results of the reviews of the application Alodokter and Halodoc. User-generated content was gathered from the platform Google Play Store in the period April to December 2020. Based on the sentiment analysis, Alodokter performs well with 73% positive and 27% negative, while Halodoc also dominated with 86% positive and 14% negative. User reviews are categorized based on three dimensions of health service quality with a multiclass classification. It is possible to identify the word networks that often appear in user reviews through text network analysis. The dimension that reviews chiefly on Alodokter and Halodoc is perceived outcome quality. The result of this study could help or use as guidance to be a reference for evaluations to improve Indonesia's quality of m-health services.