Service Quality Analysis based on Online Customer Review in Google Play Store (Study Case of Telkomsel)

Abstract

A corporation that offers internet services is known as an Internet Service Provider (ISP). Regional-scale networks and worldwide networks are offered at ISPs, allowing consumers to effortlessly connect with the outside world globally. Telkomsel is one of providers that is used the most widely in Indonesia. However, Telkomsel is also a provider with the most complaints than others. This study chooses Telkomsel as a case study to determine their quality of service based on customer review. This paper aims to analyze and identify the service quality of Telkomsel and topics that were discussed by Telkomsel users based on customer reviews in Google Play Store. We categorized the data according to the following service quality dimensions: network quality, customer service and technical support, information quality, security and privacy, and fulfillment. As a result, the Naive Bayes Classifier (NBC) was applied to assist in the sentiment analysis process. The accuracy for sentiment analysis using NBC was more than 75%. This study used Latent Dirichlet Allocation (LDA) models for topic modeling to identify themes that are often discussed by consumers. Hence, the result of this study can help a company to improve and develop their quality of product and service according to customer needs.