Analisis Opini Netizen Tentang Pergantian Pelatih Tim Sepak Bola Menggunakan TF-IDF dan Naive Bayes
DOI:
https://doi.org/10.30646/sinus.v24i2.1059Abstract
Penelitian ini bertujuan untuk menerapkan teknik penambangan teks untuk klasifikasi teks pada dataset yang dipilih. Tahapan penelitian meliputi pengumpulan data, pra-pemrosesan teks, ekstraksi fitur, pengembangan model klasifikasi, dan evaluasi kinerja. Pra-pemrosesan teks dilakukan melalui case folding, pembersihan data, tokenisasi, penghapusan stopword, dan stemming untuk meningkatkan kualitas data sebelum klasifikasi. Hasil menunjukkan bahwa model yang diusulkan mencapai kinerja yang memuaskan dengan akurasi 84,87%, sedangkan evaluasi menggunakan metrik presisi, recall, dan F1-score menunjukkan bahwa pendekatan yang diterapkan efektif dalam melakukan klasifikasi teks otomatis, meskipun terdapat variasi kinerja di berbagai kelas.
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