Sentiment Analysis of Flood Risk Opinions in Semarang City Using the K-Nearest Neighbor (KNN) Algorithm

Abstract

Flood risk is an important problem in the city of Semarang, Indonesia, which requires a deep understanding of public perception. In this research, sentiment analysis was carried out on public opinion regarding flood risk using the K-Nearest Neighbor (KNN) algorithm. Public opinion data collected from various sources, including social media, news articles, and online forums, is analyzed using natural language processing and KNN techniques to classify opinions as positive, negative, or neutral. Data related to flood risk is also used to provide relevant context. It is hoped that the results of this sentiment analysis will provide valuable insight into public perceptions of flood risk in Semarang City, which can be used to design more effective and sustainable mitigation strategies.