Cakrawala Repositori Imwi
Vol. 6 No. 2 (2023): Cakrawala Repositori IMWI

Analisis Sentiment Review Pengguna BCA Mobile Menggunakan Teks Mining

Willa Fatika Sari (Fakultas Ekonomi dan Bisnis, Universitas Andalas, Kota Padang, Indonesia)
Rida Rahim (Fakultas Ekonomi dan Bisnis, Universitas Andalas, Kota Padang, Indonesia)
Fajri Adrianto (Fakultas Ekonomi dan Bisnis, Universitas Andalas, Kota Padang, Indonesia)



Article Info

Publish Date
28 Mar 2023

Abstract

The purpose of this research is to analyze the sentiment that exists in mobile banking and what aspects are the basis for assessing user sentiment. The method used is text mining using the Naïve Bayes algorithm in Python. The type of data used is qualitative text data. Data is collected from user reviews of mobile banking applications on the Google Play Store. The results of this study found BCA Mobile has a positive sentiment with a Positive TN value of 44% with an accuracy value of 82%. As for the confusion matrix results of each sentiment class, the Precision value in the positive sentiment class is 87%, in the negative class is 79%, the Recall value of the positive class is 72%, in the negative class is 91%, and the F1-Score value of the positive and negative classes is 79% and 84%, respectively. This assessment is reviewed from several aspects of the reviews given by users such as the verification process, ease of use, security, and features presented.

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Journal Info

Abbrev

cakrawala

Publisher

Subject

Economics, Econometrics & Finance

Description

Jurnal Cakrawala Repositori IMWI focuses on publishing original research articles, reviewing articles from contributors, and current issues relating to Economics, Business and Management. The main purpose of the journal is to provide a platform for scholars, academics, and researchers to share ...