Open AccessAnalysing Service Quality of Mobile Health Platforms Using Text Analytics: A Case Study of Halodoc And Alodokter
Publication year - 2022
Publication title -
asian journal of research in business and management
Language(s) - English
Resource type - Journals
ISSN - 2682-8510
DOI - 10.55057/ajrbm.2022.4.1.14
Subject(s) - sentiment analysis , analytics , computer science , service quality , quality (philosophy) , service (business) , data science , customer satisfaction , service provider , world wide web , internet privacy , business , marketing , artificial intelligence , philosophy , epistemology
As time passes by with the technological developments that affect people’s daily activities, the health sector has become one of the sectors undergoing digital transformation. Due to the emergence of the COVID-19 virus in early 2020 which became the source of a global pandemic outbreak, there has been a surge in the use of telemedicine applications in Indonesia. This study aims to determine users’ sentiment and main topics regarding the service quality of mobile health applications through content obtained from User-Generated Content (UGC) in form of Online Customer Reviews (OCR) on Google Play Store. The research method used in this study is text analytics, by analyzing and interpreting data in the form of texts to generate insights from customers regarding the service quality of two mobile health applications, Halodoc and Alodokter. The result of this study based on sentiment analysis and topic modeling points to positive insights for service quality of both applications. However, the privacy dimension on Halodoc and Alodokter leans towards a higher percentage of negative sentiment than positive sentiment. With knowledge of service quality based on insights that emerge from customer experience regarding Halodoc and Alodokter, the two platforms could evaluate and provide better service quality for users especially their privacy to maintain satisfaction and loyalty of the applications’ users.