EVANDA, JULIANO (2022) ANALISA SENTIMEN MENGENAI SEPAK BOLA DI INDONESIA PADA TWITTER MENGGUNAKAN METODE NAIVE BAYES DAN SUPPORT VECTOR MACHINE. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
During this pandemic period, football in Indonesia has started national and international matches but is still in the monitoring stage of the COVID-19 task force. Almost all players in Indonesia have carried out procedures according to government regulations, such as vaccination and performing antigen swabs. Even spectators are not allowed to watch live inside the stadium. With the polemics that have occurred in the last few months, many opinions and opinions have emerged from social media users, one of which is Twitter. This study focuses on classifying opinions on tweets on Twitter that contain positive and negative values about footballers. In this study an experiment was conducted on a case study of football in Indonesia. This research uses two algorithms, namely Support Vector Machine and Naïve Bayes on automatic and manual labels. In automatic label testing, the best accuracy was obtained, namely the SVM algorithm with the best accuracy of 82% in the 90:10 experiment. Then the manual label obtained the best accuracy, namely the SVM algorithm with the best accuracy of 83% in the 90:10 experiment. In this study, the best algorithm for testing is the SVM algorithm on automatic labels and manual labels. Key words: Sentiment Analysis, Indonesian Football, Nave Bayes, Support Vector Machine. Di masa pandemik ini sepak bola di indonesia sudah di mulai pertandingan nasional dan international tetapi masih dalam tahap pemantauan satgas covid-19. Hampir semua pemain di indonesia sudah melakukan prokes sesuai aturan pemerintah, seperti contoh nya adalah vaksinasi dan melakukan swab antigen. Bahkan penonton saja belum di perbolehkan untuk menonton secara langsung di stadion. Dengan adanya polemik yang terjadi dalam beberapa bulan terakhir ini banyak menimbulkan opini maupun pendapat dari para pengguna media sosial salah satunya adalah twitter. Pada penelitian ini berfokus untuk mengklasifikasi terhadap opini terhadap dari cuitan di twitter yang mengandung nilai positif, negative mengenai Pesepak Bola. Pada penelitian ini melakukan eksperimen pada studi kasus Sepak Bola di Indonesia. Penelitian ini menggunakan dua algoritma yaitu Support Vector Machine dan Naïve Bayes pada label otomatis dan manual. Pada pengujian label otomatis di dapati akurasi terbaik yaiu algoritma SVM dengan akurasi terbaik yaitu 82% pada percobaan 90:10. Kemudia pada label manual di dapati akurasi terbaik yaitu algortima SVM dengan akurasi terbaik yaitu 83% pada percobaan 90:10. Pada penelitian ini pada pengujian algoritma terbaik adalah algoritma SVM pada label otomatis maupun label manual. Kata kunci : Analisis Sentimen, Sepak Bola Indonesia, Naïve Bayes, Support Vector Machine.
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 22 105 |
| NIM/NIDN Creators: | 41518010090 |
| Uncontrolled Keywords: | Analisis Sentimen, Sepak Bola Indonesia, Naïve Bayes, Support Vector Machine. |
| Subjects: | 100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 154 Subconscious and Altered States and Process/Psikologi Bawah Sadar > 154.6 Sleep Phenomena/Fenomena Tidur > 154.63 Dreams/Mimpi > 154.634 Analysis/Analisis 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | ADELINA HASNA SETIAWATI |
| Date Deposited: | 06 Oct 2022 06:41 |
| Last Modified: | 06 Oct 2022 06:41 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/70024 |
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