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All Journal Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Maria Nuzurana Asti
Universitas Bumigora

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Lexicon Based Sentiment Analysis pada Trending Topic di Nusa Tenggara Barat Ismarmiaty; Maria Nuzurana Asti; Ahmad Ashril Rizal
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 3 No 2 (2022): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v3i2.6136

Abstract

This study aims to find trending topics and conduct sentiment analysis on trending topics related to the province of West Nusa Tenggara. This analysis uses tweet data from January 1, 2019 to December 31, 2020. The method used is Lexicon Based with the python programming language. The research stages consist of crawling the dataset, preprocessing, finding trending topics, lexicon based sentiment analysis & confusion matrix test and visualization. The conclusion from the analysis related to trending topics is that the top ten trending topics that emerged include: (1) COVID-19, (2) Wistan's brother, (3) MotoGP, (4) Rimpu Culture, (5) Baturotok Village fire, ( 6) The throwing of the factory by four housewives, (7) Rocky Gerung, (8) #onehealthKIPM, (9) after the NTB earthquake, and (10) the arrival of Sandiaga Uno to Bima. Sentiment analysis results show that several topics tend to lead to positive sentiment, including: 2nd, 3rd, 4th, 5th, 8th topics, 9th and 10th topics. While the 1st topic is related to COVID-19, the 6th and 7th tend to lead to negative sentiment. The test accuracy value is above 80% and the average score for all topics is 100% on accuracy, 100% on precision and 100% on recall.
Co-Authors Ismarmiaty Rizal, Ahmad Ashril