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Willa Fatika Sari
Fakultas Ekonomi dan Bisnis, Universitas Andalas, Kota Padang, Indonesia
Economics, Econometrics & Finance

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Analisis Sentiment Review Pengguna BCA Mobile Menggunakan Teks Mining Willa Fatika Sari; Rida Rahim; Fajri Adrianto
Cakrawala Repositori IMWI Vol. 6 No. 2 (2023): Cakrawala Repositori IMWI
Publisher : Institut Manajemen Wiyata Indonesia & Asosiasi Peneliti Manajemen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52851/cakrawala.v6i2.295

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.
Analisis Sentiment Review Pengguna BCA Mobile Menggunakan Teks Mining Willa Fatika Sari; Rida Rahim; Fajri Adrianto
Cakrawala Repositori IMWI Vol. 6 No. 2 (2023): Cakrawala Repositori IMWI
Publisher : Institut Manajemen Wiyata Indonesia & Asosiasi Peneliti Manajemen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52851/cakrawala.v6i2.295

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.
Co-Authors Fajri Adrianto Rida Rahim