IMPLEMENTASI METODE KLASIFIKASI NAÏVE BAYES PADA ANALISIS SENTIMEN ULASAN APLIKASI MOBILE LEGENDS DI GOOGLE PLAY STORE
Keywords:
Analisis Sentimen, Text Mining, Naïve Bayes, Mobile Legend, Google Play StoreAbstract
Penelitian ini menerapkan metode klasifikasi Naïve Bayes untuk menganalisis sentimen ulasan pengguna terhadap aplikasi Mobile Legends di Google Play Store. Data ulasan dikumpulkan melalui teknik web scraping, lalu dilabeli dan diproses melalui tahap preprocessing, termasuk case folding, penghapusan stopwords, tokenisasi, dan stemming. Data dibagi menjadi data pelatihan dan pengujian, kemudian fitur-fitur diekstraksi menggunakan metode TF-IDF. Hasil penelitian menunjukkan bahwa model Naïve Bayes mencapai tingkat akurasi sebesar 85% dalam mengklasifikasikan sentimen ulasan. Evaluasi melibatkan presisi, recall, dan F1-score. Temuan penelitian ini memberikan wawasan yang mendalam tentang pandangan pengguna terhadap Mobile Legends dan memiliki potensi aplikasi dalam pemantauan sentimen serta pengembangan aplikasi mobile dan analisis sentimen berbasis teks di berbagai domain.
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