Analisis Sentimen Masyarakat Mengenai Aplikasi Shopeefood Menggunakan Chi Square dan Metode Naive Bayes Classifier
DOI:
https://doi.org/10.30865/klik.v3i6.927Keywords:
Chi-Square; TF-IDF; Naïve-Bayes; Shoope-Food; TwitterAbstract
In April 2020, Shopee launched a delivery service known as ShopeeFood. This service has grown into a large service platform that is in demand by various age groups. Regarding the ShopeeFood phenomenon, the public provides feedback in the form of ratings and opinions on various social media, one of which is Twitter media. The steps taken to understand the perceptions or sentiments of the ShopeeFood community, data are collected through social media and analyzed using the Naive Bayes Classifier method with the Chi feature. Rectangle. Tweet data is retrieved via the Twitter API using key terms related to ShopeeFood. The dataset contains 1050 data divided into three sentiment classes: positive, negative and neutral. The test results use Chi Square on the Naive Bayes Classifier method with a test ratio of 90:10% and produces an accuracy value of 65.71%, a precision value of 95,00 %, and the recall value is 90,00% and the test results use TF-IDF with a test ratio of 90:10% and produce an accuracy value of 79.05%, a precision value of 95,00%, and a 90,00% recall value. Based on the research results, it can be concluded that the TF-IDF feature gets higher accuracy than the Chi Square feature in the Naive Bayes Classifier method and is successful in classifying tweets with positive, negative, and neutral sentiments.
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