Pengkategorian Komentar Instagram Terhadap Layanan Akademik dan Non-Akademik Universitas Terbuka
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Abstract
Instagram is one of the social media that has many users in Indonesia, where users are free to comment on whatever is going on, including being a form of online communication between campuses and their students. The number of topics and comments on an official Instagram account can be used as evaluation or learning material. The Open University is one of the campuses that has an official Instagram account with thousands of followers. In order to get an evaluation of academic and non-academic services, in this study a categorization analysis was carried out with 10,000 comment data taken from the official @univterbuka Instagram account. The data is categorized into 7 categories, then processed using 4 algorithms, namely SVM, Naïve Bayes, Random Forest and KNN. The highest accuracy in the category of teachers with the KNN method is 98.97% and the highest AUC is in the module category with the SVM method of 94.60%.
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