Sentimen Analisis Masyarakat Di Twitter Mengenai Tragedi Stadion Kanjuruhan Berbasis K-Means Clustering

TUMIMOMOR, Rivaldo (2023) Sentimen Analisis Masyarakat Di Twitter Mengenai Tragedi Stadion Kanjuruhan Berbasis K-Means Clustering. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.

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Abstract

This study aims to explore the emotions contained in the Tweet data of public opinion users of Twitter social media. The background of this research is the tragedy that occurred on Saturday, October 1 2020 at the Kanjuruhan Stadium which claimed ± 700 victims, 132 of whom died. Kanjuruhan Stadium has become a trending topic on Twitter social media because many people have responded to this tragedy. A collection of opinions on Twitter can be analyzed to find out the emotional sentiment contained in public opinion so that it is hoped that this can become a wise and objective reference for the community so that this tragedy does not happen again. This study uses the SentiArt method for sentiment analysis and K-Means Clustering for Twitter opinion classification. The research data is a collection of Indonesian-language Tweets totaling 44,917 data taken on October 1 2022 - October 10 2022 by using the TwitterAPI based on the keywords "Kanjuruhan" and "Tragedi". The results of the study show that the largest emotional sentiment in 44,917 Tweet data is Surprise (25%) and the smallest emotion is Fear (4%). While the data is divided into 5 Clusters showing the greatest emotional sentiment on k-2 Sadness (7508.605925) and the smallest emotion on k-1 Sadness (-5770.360743), the 10 largest emotional Clusters on k-5 Sadness (7447.597249) and the smallest emotion on k-2 Sadness (-5764,930083), and 15 The biggest emotion Cluster on k-6 Sadness (7199,196867) and the smallest emotion on k-2 Sadness (-4885,612).

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