Analisis Sentimen Pelayanan Pelanggan Mini Market Alfamart Pada Media Sosial Twitter Dengan Naïve Bayes Classifier
Keywords:
Alfamart, Text Classification, Twitter, Naïve Bayes ClassifierAbstract
Twitter is one of the social media that is currently popular, here the public is free to have opinions, write, and comment on anything. PT Sumber Alfaria Trijaya with its trademark Alfamart is a company engaged in the retail sector. Not infrequently consumers submit complaints, criticisms, and suggestions through this social media. Community opinion can be used as evaluation material in improving services. In this study, sentiment analysis for Alfamart minimarket customer service was carried out based on data obtained from Twitter. This sentiment analysis aims to classify Alfamart's customer service tweets into positive, negative, and neutral sentiments using the naive Bayes classifier algorithm. The data used is 2000 tweet data and then preprocessing is carried out so that 1691 tweets are clean data. Of the 1691 data analyzed, 1017 positive tweets, 297 negative tweets, and 377 neutral tweets were obtained. Then the data will be divided into 80% training data and 20% test data. The results of the accuracy value are 70% with a Precision value of 70%, a Recall value of 70%, and an F1-Score value of 66%.
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