Analisis Sentimen Pandangan Masyarakat Terhadap Piala Dunia U-17 Menggunakan Teknik Teks Mining
Keywords:
World Cup U-17, Naïve Bayes, Support Vector Machine (SVM), World Cup U-17, Naïve Bayes, upport Vector Machine (SVM)Abstract
One of the most loved sports by people around the world is football. Indonesia is one of the countries with the most football fans in the world. Indonesia is one of the countries with the largest number of football fans in the world, with 77% of the Indonesian population interested in football. Based on research analysis, Indonesia was selected to host the 2023 U-17 World Cup. The decision was made after the International Football Federation (FIFA) granted hosting rights. Specifically to the President of the Indonesian Football Federation (PSSI). This research aims to classify public opinion related to the event from twitter social media into 3 class categories, namely neutral, positive and negative. In this research, the methods used are Naïve Bayes algorithm and Support Vector Machine (SVM) algorithm. The classification results show that the naïve bayes method has an accuracy result of 0.73 while for the Support Vector Machine method the accuracy value obtained is 0.84 which shows that Support Vector Machine has better accuracy than Naive Bayes. Based on the model classification, positive sentiment has the highest percentage of other classes with a percentage of 35%, followed by negative sentiment with a percentage of 31% and neutral sentiment is the minority class with a percentage of 33%. From the percentage obtained, it can be concluded that the public has a positive view of the organisation of the U-17 world cup in Indonesia. It is hoped that in the future this research can be improved and implemented better with additional algorithm methods or with a larger amount of data.
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