Analisis Sentimen Twitter: Penanganan Pandemi Covid-19 Menggunakan Metode Hybrid Naïve Bayes, Decision Tree, Dan Support Vector Machine
DOI:
https://doi.org/10.34818/eoe.v9i3.17984Abstract
Abstrak Indonesia menduduki peringkat keenam sebagai negara dengan pengguna media sosial Twitter terbanyak.Pada bulan Desember 2019, sebuah virus yang dijuluki COVID-19 muncul dan mulai menyebar ke hampirseluruh penjuru dunia. Penulis bermaksud untuk melakukan analisis sentimen pengguna Twitter tentang penanganan COVID-19 di Indonesia serta membandingkan hasil akurasi dari model hybrid (Stacking Ensemble) dan modelmodel individu lainnya. Model-model klasifikasi machine learning individu mempunyai kelebihan dan kekurangannya masing-masing, dan setiap modelnya mempunyai karakteristik yang berbeda dalam menjalankan proses klasifikasi. Penulis menggunakan Stacking Ensemble sebagai model klasifikasi hybrid. Stacking Ensemble bekerja dengan cara mengkombinasikan hasil prediksi dari model klasifikasi lainnya. Kemudian hasil tersebut akan dikombinasikan dengan metaclassifier (Logistic Regression) dengan tujuan untuk mendapatkan hasil prediksi akhir yang lebih akurat dibanding dengan hasil klasifikasi model tunggal. Dari penelitian ini, ditemukan bahwa reaksi umum pengguna Twitter di Indonesia terhadap penanganan COVID-19 di Indonesia secara umum adalah positif, dengan presentase sentimen positif 75.3% dan 60.39%. Sehingga, dapat disimpulkan bahwa penganganan COVID-19 di Indonesia dianggap baik oleh masyarakat Indonesia. Selain itu, ditemukan bahwa metode hybrid Stacking Ensemble dapat meningkatkan nilai akurasi yang dihasilkan oleh classifiers individu lainnya, dengan perbedaan 0.63% dan 1.02%. Kata kunci: analisis sentimen, COVID-19, hybrid, Stacking EnsembleReferences
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