Studi Sentimen Masyarakat Terhadap Layanan FLIX Cinemas di Twitter dengan Pendekatan Naïve Bayes dan SVM

Ahmad Ridlan1 Daniel Eliazar Latumaerissa2 Muhaimin Hasanudin3* Derisma Derisma4 Muhamad Fadli5
(1) Information System, Institut Teknologi dan Bisnis Stikom
(2) Information System, universita Pembangunan Nasional Veteran Yogyakarta
(3) Faculty of Computer Science, Mercu Buana University
(4) Departemen Informatika Fakultas Teknologi Informasi Universitas Andalas, Padang
(5) Faculty of Computer Science, Mercu Buana University
(*) Corresponding Author

Abstract

Penelitian ini melakukan analisis sentimen opini publik terhadap FLIX Cinemas dengan platform Twitter menggunakan metode Naïve Bayes dan Support Vector Machine (SVM). Tujuan utama dari penelitian adalah klasifikasi sentimen yang akurat - baik positif maupun negatif terkait layanan FLIX untuk memperoleh denyut respons publik terhadap layanan. Metodologi yang digunakan adalah pengumpulan twitter, praproses, pelabelan manual dan otomatis, pelabelan yang dibobot dengan TF-IDF. Klasifikasi menggunakan Naïve Bayes dan SVM dengan tiga skenario berbagi data pada 90:10, 80:20, dan 70:30. Hasilnya menyatakan bahwa SVM memiliki akurasi maksimum sebesar 92% untuk pelabelan otomatis dan Naïve Bayes sebesar 87% dalam pelabelan manual. Dari hasil penelitian ini menyatakan bahwa SVM lebih efektif untuk dataset besar sedangkan Naïve Bayes berlaku untuk data kecil sehingga dapat menjadi salah satu acuan bagi FLIX dalam upayanya meningkatkan pelayanan sesuai dengan hasil analisis sentimen

Keywords

Analisis Sentimen, Naïve Bayes, Support Vector Machine, FLIX Cinemas

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DOI: https://doi.org/10.53514/jco.v5i1.631

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