Analisis Pengaruh Faktor Persepsi Terhadap Minat Penggunaan E-Wallet Shopee-Pay

Abstract

ABSTRAK 

Shopeepay is an electronic money service issued by the Shopee company for transactions on Shopee, offline payments at Shopee Pay partners and storing returned funds for use in subsequent transactions. The large number of Shopeepay users in Indonesia has given rise to many opinions about this platform, one of which is the microblogging site, namely Twitter. Sentiment analysis or opinion mining is computational learning to identify and extract and study opinions, sentiments, emotions, judgments and views in text form. Random Forest is a method for conducting sentiment analysis and is a type of Decision tree method. In this study, the random forest classifier algorithm was used to classify Twitter users' opinions on the Shopeepay platform. From its application, the resulting value for depth results with 55 trees and 300 trees resulted in a precision value of 95%, recall 94%, F1-Score 95% and accuracy 95%. Data analysis shows that positive and significant perceptions of usefulness have a positive effect on interest in reusing the Shoppe Pay e-wallet. In this research, it shows that the interest of students at the University of 17 August 1945 Samarinda in using the Shopee-Pay e-wallet is very positive both in using transactions. Someone will be able to reuse a technology if he feels that the technology is able to help improve performance effectiveness or is useful and how to use it is easy to understand and has minimal risks.