Klasifikasi Topik Twitter Menggunakan Metode Random Forest Dan Fitur Ekspansi Word2vec
DOI:
https://doi.org/10.34818/eoe.v9i1.17391Abstrak
Pengguna social media Twitter biasanya hanya tertarik pada tweet yang termasuk dalam jenis topik tertentu. Tweet yang hanya memuat tidak lebih dari 140 karakter, membuat klasifikasi tweet menjadi banyak tantangan, karena tweet yang pendek, noice, dan kurang fokus pada topik. Solusi untuk menyelesaikan tantangan tersebut dalam penelitian ini menggunakan fitur ekspansi agar memperkaya teks sehingga tampak seperti dokumen teks berukuran besar. Metode yang dipilih pada fitur ekspansi adalah Word2Vec, untuk mengelompokkan vektor dari kata-kata yang mirip menjadisatu di dalam ruang vektor, artinya mendeteksi kemiripan secara matematis. Penulis menggunakan metode Random Forest untuk klasifikasi data tweet pada penelitian ini, karena terkenal karena menjaga ketidak seimbangan data di kelas yang berbeda, terutama kumpulan data yang sangat besar. Kata kunci : Tweet, Fitur Ekspansi, Word2Vec, Random ForestReferensi
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