Klasifikasi Emosi Supporter Persebaya Di Twitter Dengan Metode Long Short Term Memory(Lstm)
DOI:
https://doi.org/10.29407/1ak10b76Abstract
Twitter menjadi ruang aktif bagi pendukung Persebaya Surabaya untuk menyuarakan opini dan emosi mereka. Penelitian ini bertujuan untuk mengklasifikasikan sentimen komentar pendukung di Twitter ke dalam kategori positif, negatif, dan netral. Data diperoleh melalui pengumpulan komentar twitter, kemudian dilabelo menggunakan TextBlob dan divalidasi oleh dosen bahasa. Setelah melalui tahapan preprocessing dengan stemmer Sastrawi dan representasi word embedding, data dianalisis menggunakan model Long Short-Term Memory (LSTM). Hasil menunjukkan bahwa model mampu mengklasifikasikan sentimen dengan cukup akurat, meskipun masih terdapat kendala dalam memahami kritik halus atau konteks implisit. Penelitian ini diharapkan dapat menjadi landasan dalam memahami opini publik terhadap klub serta mendorong pengembangan sistem analisis sentimen di ranah olahraga dan media sosial berbahasa Indonesia.
Keywords:
Analisis Sentimen, LSTM, Twitter##plugins.themes.default.displayStats.downloads##
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