Abstract

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.

Highlights

  • an activity that is in great demand

  • of the sporting events held in the Southeast Asia region

  • The most SEA Games issues occurred on Twitter with 20,600 tweets

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Summary

Pendahuluan

Olahraga merupakan salah salatu unsur yang berpengaruh dalam kehidupan manusia yang ikut berperan dalam mengharumkan nama daerah dan bangsa baik melalui kompetisi regional, nasional maupun internasional. Variabel yang digunakan oleh peneliti berasal dari media sosial twitter tentang opini masyarakat mengenai objek wisata dunia fantasi sebanyak 100 data yang dibagi menjadi dua jenis yaitu 50 data review positif dan 50 data review negatif [9]. Variabel yang digunakan oleh peneliti berasal dari media sosial twitter tentang opini masyarakat mengenai penyedia layanan telekomunikasi seluler sebanyak 300 data yang dibagi menjadi dua jenis yaitu data dengan perbandingan 70% untuk data latih dan 30% untuk data uji [10]. Berdasarkan latar belakang yang sudah dipaparkan, maka peneliti ingin meneliti tentang komentar netizen twitter terhadap Southeast Asian Games (SEA Games) di Filipina tahun 2019 menggunakan k-nearest neighbor dan support vector machine. Tujuan dari penelitian ini adalah mendapatkan dan membandingkan hasil ketepatan klasifikasi sentimen pengguna twitter terhadap Southeast Asian Games (SEA Games) di Filipina tahun 2019 menggunakan k-nearest neighbor dan support vector machine

Tinjauan Pustaka
Support Vector Machine
Sumber Data dan Variabel Penelitian
Hasil dan Pembahasan
Simpulan dan Saran
Full Text
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