Analisis Sentimen pada Twitter Berbahasa Indonesia Terhadap Penurunan Performa Layanan Indihome dan Telkomsel
DOI:
https://doi.org/10.26418/justin.v10i4.50858Keywords:
Analisis Sentimen, Naïve Bayes Classifier, Python, Snscrape, Text Mining, TwitterAbstract
Opini masyarakat yang dituliskan dalam sebuah jejaring sosial Twitter dapat dimanfaatkan sebagai bahan dalam proses analisis sentimen yang dapat diklasifikasikan ke dalam sentimen positif dan negatif. Analisis Sentimen atau Opinion Mining adalah bagian dari studi ilmu Text Mining yang proses utamanya adalah mengambil dataset mentah dan kemudian mengekstrasi dataset tersebut menjadi sebuah informasi bermanfaat yang bersifat sentimen terhadap suatu permasalahan objek atau topik apakah cenderung ke dalam kalimat positif, atau bahkan negatif. Penelitian memanfaatkan jejaring sosial media Twitter dalam prosesnya yang bertujuan untuk mengklasifikasikan data tweets berbahasa Indonesia menjadi sentimen positif dan negatif. Proses pengambilan data menggunakan Bahasa Pemrograman Python dengan memanfaatkan library snscrape. Data yang digunakan dalam penelitian ini dilakukan proses klasifikasi data tweets menggunakan algoritma Naïve Bayes Classifier. Setelah dilakukan pengujian dengan metode Naïve Bayes Classifier, didapatkan hasil akurasi sebesar 96%, precision 96%, recall 96%, dan fi-score 95%.
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