Analisis Sentimen Pengguna Aplikasi CapCut Pada Ulasan di Play Store Menggunakan Metode Naïve Bayes
DOI:
https://doi.org/10.30865/klik.v4i4.1555Keywords:
CapCut; Naïve Bayes; Confusion Matrix; Play Store; Sentiment AnalysisAbstract
There is an increasing interest in sharing experiences displayed in video visualizations, creating a demand for efficient and simple editing tools. CapCut is an all-in-one creative digital platform that enables video editing on browser, desktop and mobile. The CapCut app is one of the most downloaded apps on the Play Store with 500 million downloads and is available for free. CapCut app is perfect for beginner editors as it has a simple interface with various interesting features such as templates that are easy to operate without the need for additional software. However, this cannot guarantee the satisfaction of its users. Various experiences that are felt affect the assessment given by users. Sentiment analysis is important to determine the level of user satisfaction, the results of which can be used as a reference for improving the quality of the application. To find out user reviews of the CapCut application, sentiment analysis is carried out using the Naïve Bayes method with the aim of knowing the number of positive and negative sentiments from user reviews. The data used is taken from the review column available on the Play Store using web scrapping techniques with the help of Google Colab as much as 880 user review data. The data is divided into 60% training data which is 528 reviews and 40% test data which is 352 reviews. The analysis resulted in 30 more negative sentiments than positive sentiments with the number of negative sentiments totaling 455 reviews and the number of positive sentiments totaling 425 reviews. Based on the evaluation using confusion matrix, the accuracy result is 84.09%, precision is 91.91%, and recall is 73.53%.
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