ANALISIS SENTIMEN PADA SOSIAL MEDIA INSTAGRAM MENGGUNAKAN ALGORITMA NAIVE BAYES (STUDI KASUS : TIMNAS FUTSAL INDONESIA) - Doli Ananda Efraim (2023)
Social media has become a new identity for Indonesian people today and is also a lifestyle that is difficult to forget. Along with the times, social media has spread widely on the internet, and every user has the freedom to use social media as they wish. In fact, many users have more than one social media account. One of the popular social media platforms is Instagram, which can be accessed via Android and iOS smartphones, as well as through the website. The initial stage in this research was collecting comment data taken from Instagram social media. Then the comment data is labeled positive and negative which will be given by 2 annotators. After that, pre-processing is carried out such as data cleaning, case folding, normalization, tokenization, stopword removal, and stemming then weighting words with Term Frequency - Inverse Document Frequency. The results of data labeling amounted to 262 positive comments and 142 negative comments. Then the data is divided into 80% training data and 20% test data. The algorithm used to perform the classification is naive Bayes. The classification results obtained are accuracy of 71%, precision of 84%, recall of 69%. Keywords: Sentiment Analysis, Indonesian Futsal National Team Posts, Naïve Bayes, Instagram