IMPLEMENTASI ALGORITMA NAÏVE BAYES TERHADAP ANALISIS SENTIMEN PADA TIMNAS BULU TANGKIS INDONESIA DI JEJARING SOSIAL TWITTER - Alpin Anugerah (2023)
Social networks are not only useful as an effective medium of communication, but social networks can also be a place to accommodate opinions or opinions among the general public. One social network that is widely used to accommodate these opinions is Twitter.users Twitter in Indonesia often express their opinions on all fields including sports, especially the Indonesian Badminton National Team. There are various kinds of opinions about the Indonesian Badminton National Team, which can be seen on Twitter. Based on these conditions, research was carried out on public opinion about the Indonesian Badminton National Team. One way to do this is to carry out a sentiment analysis of the Indonesian Badminton National Team on the Twitter using the classification method and the Naïve Bayes to classify positive or negative tweets that people express about the Indonesian Badminton National Team. The amount of data that was crawled was 3,277 data and then the data went through a data duplicate removal so that the results obtained were 272 data tweets and had not been labeled. Prior to the process of classifying the data obtained, the data must be labeled on the data as well as cleaning the data first before entering the text processing, then the data will be weighted for each word with the Term Frequency- Inverse Document Frequency (TF-IDF) which will be said in the future. will be used as a feature. Then, because the data labeled positive and negative have a much different amount, the Synthetic Minority Oversampling Technique (SMOTE) method is used to carry out balancing of the data. The next stage is the implementation of the distribution of data whose magnitude is 80% 20% and is classified using the Naive Bayes method. Then the results obtained from the implementation of this research are that the test data obtained accuracy with a percentage of 96%, precision with a percentage of 100%, recall with a percentage of 92%.