ANALISIS SENTIMEN PENGGUNA TWITTER TERHADAP APLIKASI MYPERTAMINA MENGGUNAKAN METODE K-NEAREST NEIGHBOR DENGAN SELEKSI FITUR CH-SQUARE
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Date
2023-03
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Publisher
Elfitra
Abstract
Pertamina announced a trial policy for using the MyPertamina application for targeted
distribution of subsidized fuel in June 2022. This trial was carried out in 11 regions
started on July 1, 2022. This policy had been widely discussed on social media Twitter,
so there are pros and cons from the community. The large number of public responses
in the form of tweets on Twitter requires a sentiment analysis to see an overview of the
public's perception of the MyPertamina application. This study used the K-Nearest
Neighbor algorithm to classify the public's response to the policy in the form of positive
or negative sentiment. This study also added the Chi-Square selection feature to
determine the effect on the performance of the K-Nearest Neighbor algorithm. This
study used the Python programming language with 2923 tweets as a dataset which had
a proportion of 73% positive sentiment and 27% negative sentiment. The research used
ratio of 80:20 to the dataset, namely 80% of the training data is 2338 and 20% of the
testing data is 585. The resulted of the research on the K-Nearest Neighbor algorithm
used K-Fold Cross Validation for 10 broadcasts produced the same average accuracy,
namely 77% for both methods, which had the highest accuracy of 88% for K-Nearest
Neighbor with Chi-Square and 87% accuracy without used Chi-Square.
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Keywords
Sentiment analysis, Chi-Square, K-Nearest Neighbor, MyPertamina, Twitter
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