Analisis Sentimen Masyarakat Terhadap Kondisi Perekonomian di Indonesia Pada Masa Pandemi 2020
Abstract
Masyarakat Indonesia banyak yang memperbincangkan isu ekonomi Indonesia pada masa pandemi Covid-19 2020 di media sosial. Salah satu isu yang diperbincangkan yaitu mengenai resesi Indonesia dimana sudah ada masyarakat yang memperbincangkan hal ini di media sosial sebelum Indonesia mengalami resesi. Masyarakat yang khawatir dan membahas isu ekonomi ini lebih cenderung untuk menuangkan opini negatif di media sosial. Untuk itu dibuat analisis sentimen data opini publik mengenai ekonomi Indonesia di media sosial khususnya twitter. Sehingga dapat diklasifikasikan sentimen setiap opini dan mempermudah mendeteksi isu ekonomi yang ada pada kumpulan opini publik yang bersentimen negatif. Dan dapat dianalisa dan dijadikan acuan oleh pihak yang memerlukan apakah memerlukan penanganan atau tidak. Klasifikasi sentimen pada penelitian ini dibuat menggunakan algoritma Naïve Bayes, Support Vector Machine, dan K-Nearest Neighbor dengan menggunakan metode cross validation 10 fold dengan 3 skenario random percentage split. Dari hasil evaluasi dari ketiga model tersebut diketahui bahwa algoritma Support Vector Machine dengan percentage split 90:10 memiliki kinerja paling baik yang menghasilkan akurasi sebesar 95,53%.References
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