Analisis Sentimen Masyarakat terhadap Isu New Normal Scenario berdasarkan Opini dari Twitter menggunakan Algoritma Naive Bayes Classifier - Muhammad Nurhuda Rusardi; Bayu Rahayudi; Putra Pandu Adikara (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
The COVID-19 pandemic has spread to various countries around the world, the country of Indonesia has not escaped the ferocity of the COVID-19 pandemic, the rate of positive cases in Indonesia has experienced an increase. The government has taken various ways to suppress positive cases of COVID-19, one of which is the implementation of the New Normal. Twitter is a social media that is widely used by Indonesian people in many ways. Topics regarding the New Normal can appear on Twitter's trending topic feature because many Indonesians discuss the implementation of the New Normal in Indonesia, various opinions regarding the implementation of the New Normal scenario in Indonesia will be obtained using text mining techniques by using the Twitter API crawling, the texts data must go through data cleaning process to make easy classification process by using Naive Bayes Classifier method. At first, the data have been labelled to ease the sentiment analysis process. The last process is classification process by using Naive Bayes Classifier method. After the classification process, the predicted sentiments are evaluated using 5-fold cross validation and confusion matrix. This research yields average accuracy 0,86, precision, 0,86, recall 0,86, and f-measure 0,86.