Sentiment Analysis on Android Applications using MediaPipe for Text Classification - Ardika, Kadek Febry; Santoso, Joko Dwi (Sistemasi: Jurnal Sistem Informasi, 2025)
Sentiment analysis is an important process for understanding public opinion on various issues discussed on social media. This study aims to develop an Android application that utilizes MediaPipe for text classification based on sentiment. MediaPipe is used as a framework for feature extraction, which is then analyzed using machine learning models. The study employs a real-time design approach to support efficient text processing on devices with limited resources. The testing results show that the application achieves high accuracy in classifying positive, negative, and neutral text. These findings suggest that MediaPipe can be an effective solution for sentiment analysis on mobile devices. This research makes a significant contribution to public opinion analysis technology by introducing an efficient, adaptive, and scalable approach.