Sentiment Analysis Of Development Jakarta-Bandung High-Speed Train Using Twitter Social Media With BNN Method

Abstract

The Jakarta-Bandung high-speed train is one of the infrastructure development projects currently being carried out by the Indonesian government. The project is a large project that requires a long processing time and very large costs. Therefore, infrastructure development has reaped a lot of public opinions, both positive and negative. The purpose of writing this Final Project is to analyze sentiment on public opinion about the construction of the Jakarta-Bandung high-speed train. With data sourced from Twitter social media, the data will be analyzed in three classes, namely positive, negative, and neutral classes where the weighting will use the TF-IDF. The classification method used in this study is the Backpropagation Neural Network method. The best results were obtained in this study using a hyper tuning scenario with an accuracy of 74.56%.