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All Journal Prosiding Snastikom
Nurcholis Geofany
Universitas Harapan Medan
Computer Science & IT Library & Information Science

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Klasifikasi Sentimen Tweet Pada Twitter Terhadap Pembelajaran E-Learning Menggunakan Metode k-Nearest Neighbor Nurcholis Geofany; Tommy; Risko Liza
SEMINAR NASIONAL TEKNOLOGI INFORMASI & KOMUNIKASI Vol. 1 No. 1 (2021): Prosiding Snastikom 2021
Publisher : Universitas Harapan Medan

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Abstract

Indonesia is one of the most active Twitter users, so Twitter can be used as a medium to analyze e-learning topics. Studying at school is one of the things that have been affected by the current Covid-19 pandemic. On March 4, 2020, UNESCO (United Nations Educational, Scientific and Educational Organization) recommended that schools adopt a distance education system that allows teachers to reach students remotely and limits educational disruption on social networks. This study aims to answer public opinion that focuses on social media Twitter on this online/distance learning policy. Sentiment analysis is conducted to determine whether opinions on an issue have a positive, neutral, or negative trend value and can be used as a benchmark to improve a service. Sentiment analysis using the k-Nearest Neighbor method with Twitter data as much as 7800 tweet data that has been previously processed and achieves the best accuracy value of 53.03% with a comparison of training data and test data of 80:20.
Co-Authors Risko Liza Tommy Tommy