Analisis Sentimen Terhadap Aplikasi Pospay Menggunakan Algoritma Support Vector Machine dan Naive Bayes - Lubis, Ardini Yuanita; Setyawan, Muhammad Yusril Helmi (Jurnal Teknologi Dan Sistem Informasi Bisnis, 2024)
In the era of business transformation, companies are intensively striving to adapt to the developments in digital technology to enhance operational efficiency and productivity. Pospay application is one form of digital transformation by PT Pos Indonesia, where its presence will impact the improvement of the company's productivity. This research focuses on sentiment analysis of the Pospay application on the PlayStore platform. By applying machine learning methods such as Support Vector Machine (SVM) and Naive Bayes, this study aims to provide solutions to the challenges of data complexity and heterogeneity. The results show a high percentage of accuracy (88% for Naive Bayes and 87% for SVM) in classifying user sentiments with a more dominant negative tendency. These findings provide valuable insights for companies to enhance the quality of their digital services. Keywords: Sentiment, Pospay, Support Vector Machine, Naive Bayes, PlayStore