Analisis Sentimen Pengguna Twitter terhadap Pembayaran Cashless menggunakan Shopeepay dengan Algoritma Random Forest

Thifal Fadiyah Basar (Fakultas Ilmu Komputer, Universitas Brawijaya)
Dian Eka Ratnawati (Fakultas Ilmu Komputer, Universitas Brawijaya)
Issa Arwani (Fakultas Ilmu Komputer, Universitas Brawijaya)

Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 6 No 3 (2022): Mei 2022

Shopeepay is an electronic money service issued by the shopee company for transactions at shopee, offline payments at shopeepay partners, and storing the returned funds for use in subsequent transactions. Many shopeepay users in Indonesia raise many opinions on this platform, one of which is the microblogging site, namely Twitter. Sentiment analysis or opinion mining is computational learning to identify and extract as well as study opinions, sentiments, emotions, judgments and views in text form. Random Forest which is one of the methods in conducting Sentiment Analysis and enters the type of Decision tree method. In this study, the random forest classifier algorithm was used to classify the opinions of twitter users on the shopeepay platform. From the implementation, the values ​​for the results with a tree depth of 55 and the number of trees 300 resulted in 95% precision, 94% recall, 95% F1-Score and 95% accuracy.