Penerapan Metode Naïve Bayes Classifier Untuk Mendeteksi Emosi Pada Komentar Media Sosial

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Erfian Junianto
Rizal Rachman

Abstract

Keadaan psikologis yang dimiliki setiap orang diantaranya adalah emosi. Keadaan tersebut juga digunakan untuk membentuk hubungan atau menyampaikan pesan antara penulis dengan pembaca. Penetrasi internet yang semakin tinggi membuat gaya hidup masyarakat semakin berubah. Gaya hidup semakin terpengaruh oleh media sosial, sehingga membuat penyampaian informasi dan gagasan menjadi sangat bebas. Informasi dan gagasan tersebut selalu mengandung emosi dari penulisnya. Baik emosi marah, takut, bahagia, ataupun sedih. Pada penelitian ini akan diterapkan model text mining untuk melakukan deteksi melalui proses klasifikasi. Metode yang digunakan adalah naive bayes classifier. Sedangkan dataset yang digunakan sudah diberikan kelas oleh peneliti sebelumnya menggunakan best-worst scaling. Tantangan dari dataset ini adalah melakukan dari kalimat atau teks ke dalam 4 kategori emosi yaitu anger, fear, joy, dan sadness. Dari beberapa penelitian sebelumnya metode naive bayes classifier mampu menghasilkan akurasi yang cukup tinggi. Dengan diterapkan pada dataset emosi yang mempunyai karakter berbeda dari dataset kebanyakan, metode tersebut masih mampu memberikan kinerja yang baik dalam klasifikasi.


Kata Kunci:Text Mining, Klasifikasi, Deteksi Emosi, NaïveBayes Classifier

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