Sentiment Analysis of User Reviews on Line Bank Digital Application Using Support Vector Machine

Rizki Daffa Muttaqin; Ulfa Khaira; Daniel Arsa

doi:10.32664/smatika.v16i01.1762

Penulis

Rizki Daffa Muttaqin Universitas Jambi
Ulfa Khaira Universitas Jambi
Daniel Arsa Universitas Jambi

DOI:

https://doi.org/10.32664/smatika.v16i01.1762

Kata Kunci:

Line Bank, Sentiment Analysis, Support Vector Machine, User Reviews

Abstrak

With the increasing popularity of digital banking, user reviews are becoming an important source of data to understand user experiences and sentiment towards the services provided. Line Bank, as a digital bank, also receives various reviews from its users which reflect both satisfaction and dissatisfaction with their services. The problem at hand is how to analyze sentiment from user reviews effectively and accurately to provide better insight into Line Bank's service quality. This research uses the Support Vector Machine machine learning algorithm to analyze the sentiment of Line Bank user reviews. The performance of both methods is evaluated based on the metrics of accuracy, precision, recall, and F1-score. Testing was carried out with several data split scenarios, and the results showed that the Support Vector Machine had good performance. In the 90:10 data sharing scenario, Support Vector Machine achieved 89.61% accuracy. Apart from that, Support Vector Machine also shows good performance in precision, recall and F1-score metrics. Visualization analysis of the results shows the dominance of negative sentiment in Line Bank user reviews, which indicates there is room for service improvement.

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