Sports events are an activity that is in great demand, especially the people of Southeast Asia. One of the most prestigious sporting events in the Southeast Asian region is the Southeast Asian Games (SEA Games). SEA Games is one of the sporting events held in the Southeast Asia region and is only held every two years involving eleven member countries of the Association of South East Asian Nations (ASEAN). The most SEA Games issues occurred on Twitter with 20,600 tweets. This is because the 2019 SEA Games event in the Philippines experienced many irregularities, one of which is the Rizal Memorium stadium, which has not been renovated until now. The purpose of this study is to obtain and compare the results of the accuracy of the classification of Twitter users' sentiments towards the 2019 SEA Games in the Philippines using k-nearest neighbor and support vector machine. The data used in this study comes from data from Twitter social media users who often use the hashtag "SEA Games 2019" which has been done with text preprocessing of 2697 tweets with data partitions of 60% for training data and 40% for testing data. The conclusion that can be drawn from this research is that the best accuracy results in the k-nearest neighbor and support vector machine classification are the support vector machine classification with a polynomial kernel of 92.96% so that the predictions of the Support Vector Machine classification tend to be negative.
Virus COVID-19 telah menyebar ke seluruh dunia sehingga berdampak terhadap berbagai sektor. Salah satunya adalah sektor pendidikan. Sektor pendidikan di Indonesia menerapkan belajar dari rumah yang mengakibatkan dunia pendidikan belum sepenuhnya kembali sehingga tak lepas dari permasalahan biaya UKT yang masih berjalan ditambah dengan biaya kuota internet yang mahal untuk kuliah online. Tujuan dari penelitian ini adalah mendapatkan hasil ketepatan klasifikasi persepsi pengguna twitter terhadap tuntutan keringanan pembayaran UKT pada masa pandemi COVID-19 menggunakan k-nearest neighbor. Data yang digunakan pada penelitian ini berasal dari data pengguna media sosial Twitter yang sering menggunakan hashtag “Mendikbud dicari Mahasiswa” yang sudah dilakukan data filtering dan cleansing sebesar 2768 tweets dengan partisi data sebanyak 70% untuk data training dan 30% untuk data testing. Kesimpulan yang dapat dikemukakan pada penelitian ini adalah netizen twitter memiliki persepsi negatif tentang tuntutan keringanan pembayaran UKT pada masa pandemi COVID-19. Netizen twitter yang berpendapat tentang tuntutan keringanan pembayaran UKT pada masa pandemi COVID-19 lebih banyak menggunakan kata “mendikbuddicarimahasiswa”, “kampus” dan “ukt” dalam satu kali tweet. Nilai k (kelompok) sebanyak 2 merupakan nilai k yang optimum dengan nilai akurasi sebesar 83,25%.
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