Analisis Sentimen Ulasan Aplikasi KLC2 pada Google Play Store menggunakan Algoritma Naïve Bayes Classifier (NBC)

Abstract

Learning in the digital era through various platforms is widely used in companies, private organizations, and government. KLC2 was developed into a knowledge management system platform at the Ministry of Finance. KLC2 presents learning information through training organized by the Education and Training Center at BPPK. Various activities can be attended through KLC2. KLC2 can be downloaded via the Google Play Store. One of the essential features of applications on the Google Play Store is reviews, which can be used by users to rate and provide opinions in the form of review text about the application they are using. A popular method that is often used to convey ideas and feelings about service applications is reviewed. Sentiment analysis is the process of classifying text into several classes, such as positive, negative, or neither. This research aims to analyze the sentiment of KLC2 application reviews on the Google Play Store. The data source uses primary data from the Google Play Store and is analyzed using NBC. The research results show that the accuracy rate is 94%. Meanwhile, 83% of reviews were positive, 13% were negative, and 4% were neutral.