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All Journal UNP Journal of Statistics and Data Science
Aurumnisva Faturrahmi
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Sentiment Analysis of Prabowo Subianto as 2024 Presidential Candidate on Twitter Using K-Nearest Neighbor Algorithm Aurumnisva Faturrahmi; Zamahsary Martha; Yenni Kurniawati; Fadhilah Fitri
UNP Journal of Statistics and Data Science Vol. 1 No. 5 (2023): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol1-iss5/101

Abstract

The presidential election is one of the most talked topics at this moment. Based on many surveys, Prabowo Subianto is one of the strongest candidates for the upcoming 2024 presidential election. This research aims to see how the public sentiment towards Prabowo Subianto as the presidential candidate tends to be positive or negative. Sentiment classification was conducted using the K-Nearest Neighbor (KNN) algorithm. This algorithm classifies sentiment based on the k value of the nearest neighbor. This analysis was conducted in several stages such as data collection, text preprocessing, data labelling, data classification using the KNN algorithm, and evaluating the accuracy of the model in classifying sentiment. In this research, the results of the sentiment classification were 2731 positive sentiments and 76 negative sentiments. Where the accuracy rate produced by the model using the value of k = 3 on the division of training data and testing data of 80:20 is 97,33%.
Co-Authors Fadhilah Fitri Yenni Kurniawati Zamahsary Martha