Analisis Sentimen Pengguna TikTok Terhadap Progres Pembangunan IKN Menggunakan LSTM dan FastText

Abstract

The development of the Capital City of the Archipelago (IKN) is one of the national strategic projects that has generated various reactions and public opinions. Social media, especially TikTok, has become an important platform for people to voice their views through video content and interactive comments. This research aims to analyze the sentiment of TikTok users towards the progress of IKN construction using a deep learning approach, namely the Long Short-Term Memory (LSTM) algorithm. Sentiment data was collected from Kaggle as many as 1472 Indonesian comments, then processed through the stages of normalization, tokenization, and conversion into word embeddings. The LSTM model was designed and trained to classify sentiment into positive, negative, and neutral. The results of the analysis are expected to provide a comprehensive picture of public perception towards IKN, identify critical issues that are often discussed, and measure the level of public acceptance or rejection of this project. This research is expected to contribute to a better understanding of the dynamics of public opinion in the digital era.