Service Quality Analysis of Tokopedia Application Using Text Mining Method

Abstract

Shopping transformation using online applications makes it easier for sellers and buyers to make transactions. In Indonesia, there are several shopping applications, Tokopedia is one of them. Tokopedia is one of the shopping applications developed in Indonesia. To ensure users’ loyalty to the Tokopedia application, quality analysis is done to determine how the application could be improved or developed. This study applied the Quality Measurement Theory to examine the mobile shopping application service quality with three variables: interaction quality, environmental quality, and outcome quality. The data used in this study are users’ reviews of the Tokopedia application on the Google Play Store website. Data retrieval is done by scrapping for the period June 2020 to December 2020 with a total data of 21,616 reviews. The review data is then analyzed using the text mining method. The sentiment analysis results indicated a value of 65% positive sentiment and 35% negative sentiment. In multi-class classification, the results were 16% interaction quality, 26% environment quality and 58% outcome quality. The text network analysis determined how the word network was formed and uncovered negative words mentioned in each indicator in the mobile apps service quality.

Exploring network security threats through text mining techniques: a comprehensive analysis

“…This attack is carried out by sending many requests to the server, causing the service to slow down or even stop completely. In addition, malware attacks are also a frequent security threat [9], [10]. Malware is a malicious program that can damage or steal data from a computer system.…”