Penerapan Text Mining Dengan Algoritma Random Forest Menganalisis Sentimen Ulasan SATUSEHAT Mobile
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Abstract
Aplikasi SATUSEHAT Mobile merupakan hasil transformasi dari PeduliLindungi yang dikembangkan oleh Kementerian Kesehatan (Kemenkes) sebagai platform untuk menyebarkan informasi dan program kesehatan kepada masyarakat. Dengan lebih dari 1 juta ulasan dan nilai rating 3,7 bintang di Google Play Store, penting untuk menganalisis sentimen ulasan pengguna guna memahami pandangan pengguna terhadap aplikasi dan untuk meningkatkan kualitas aplikasi tersebut. Melalui pendekatan metode Teknik Text Mining, data ulasan pengguna dieksplorasi menggunakan algoritma pembelajaran mesin. Algoritma Multinomial Naive Bayes, K-Nearest Neighbors dan Decision Tree digunakan untuk membandingkan kinerja Random Forest dalam menganilisis sentimen ulasan pengguna tersebut. Hasilnya penelitian menunjukkan bahwa algoritma Random Forest memberikan analisis sentimen ulasan pengguna dengan tingkat akurasi tertinggi, sementara algoritma K-Nearest Neighbors (KNN) memiliki tingkat akurasi terendah. Penelitian ini memiliki relevansi penting dalam meningkatkan kualitas aplikasi SATUSEHAT Mobile berdasarkan pandangan dan umpan balik ulasan pengguna.
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References
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