Analisis Sentimen Pengguna Twitter Terhadap Kasus COVID-19 di Indonesia Menggunakan Metode Regresi Logistik Multinomial
DOI:
https://doi.org/10.26418/justin.v11i2.57449Keywords:
Covid-19, Analisis Sentimen, Regresi Logistik Multinomial, TwitterAbstract
Seiring berkembangnya Coronavirus Disease 2019 (COVID-19) di Wuhan dan berkembang di seluruh negara khususnya di Indonesia. Banyak masyarakat di Indonesia menuangkan dan mengekspresikan opini mereka pada media sosial salah satunya Twitter. Opini tersebut menjadi acuan pada penelitian ini untuk menganalisis sentimen masyarakat Indonesia terhadap kasus COVID-19. Analisis sentimen merupakan proses pengolahan data tekstual secara otomatis untuk mendapatkan informasi sentimen yang terkandung pada tweet. Implementasi sistem dilakukan dengan mengklasifikasi tweet menggunakan metode Regresi Logistik Multinomial. Metode Regresi Logistik Multinomial dikenal dengan regresi logistik dengan variabel dependen mempunyai skala nominal lebih dari dua kategori. Tweet diklasifikasi menjadi 3 kategori sentimen yaitu sentimen positif, netral dan negatif. Sistem analisis sentimen berbasis website menggunakan bahasa pemrograman Python. Proses analisis sentimen melalui beberapa tahapan, pertama proses crawling data tweet, kemudian hasil crawling akan diproses ke tahap text preprocessing, setelah melewati text preprocessing tweet akan dibobot menggunakan TF-IDF, kemudian tweet diklasifikasi dengan menggunakan metode Regresi Logistik Multinomial ke dalam kelas sentimen positif, netral, atau negatif. Pengujian dilakukan menggunakan 870 data tweet yang telah dilabel terlebih dahulu. Sistem analisis sentimen menghasilkan akurasi sebesar 64%, dengan precission untuk sentimen positif 85%, netral 56%, dan negatif, 53% dan recall untuk sentimen positif 74%, netral 67%, dan negatif 50%.References
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