CD Skripsi

Analisis Sentimen Dengan Metode Support Vector Machine Terhadap Ulasan Film Melalui Media Sosial Twitter

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X formerly known as Twitter is one of the most popular social media which often used by the user to post and shared their opinion about certain topic that is trend around the world with the feature named Thread. One of the topic that is usually being the trend topic is movie industry, and the movie that is the discussed right now is Oppenheimer. Twitter user can share their opinion whether it is a positive or a negative comment in the thread, which can influence other user perspective of the discussed movie. One of the effective method to gain and extract this information is through Sentiment analysis. This study employs Support Vector Machine (SVM) algorithm to classify sentiments related to the Oppenheimer film. The results show that the SVM model achieves its highest accuracy of 78,19% using the Linear kernel, while the lowest accuracy of 76,02% is from the Radial Basis Function (RBF) kernel. Predicted sentiments from 1.054 collected comments reveal that 974 are classified as positive, while 80 are classified as negative.

Keywords: Oppenheimer, Sentiment Analysis, Support Vector Machine, Twitter

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1803113302

Penerbit

Pekanbaru : Universitas Riau FMIPA Sistem Informasi., 2024

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1803113302

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

Mutia

Versi lain/terkait

Lampiran Berkas

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