Prediksi Retweet Berdasarkan Konten dan Berbasis Pengguna dengan Metode Seleksi Classifier

Muhamad Febiansyah, Jondri Jondri, Indwiarti Indwiarti

Abstract


Perkembangan media sosial telah mengubah cara penyebaran informasi secara drastis. Twitter, sebagai salah satu platform utama, memiliki peran penting dalam proses ini, dengan jutaan pengguna dan retweet yang terjadi setiap hari. Penelitian ini bertujuan untuk mengembangkan model prediksi retweet pada Twitter, memanfaatkan fitur content-based dan user-based. Metode classifier selection digunakan untuk memilih model terbaik, dengan eksplorasi berbagai teknik seperti oversampling. Hasil eksperimen menunjukkan bahwa penggunaan teknik-teknik tersebut dapat meningkatkan kinerja model dalam memprediksi retweet, terutama pada fitur user based. Meta learner dengan oversampling data pada fitur content based menunjukkan kinerja baik, penggunaan meta learner dan oversampling data memberikan dampak yang signifikan terhadap hasil penelitian

Keywords


Twitter; Seleksi Pengklasifikasi; pengambilan sampel berlebihan; Memprediksi; Pembelajar Meta

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DOI: https://doi.org/10.30591/smartcomp.v14i1.7166

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