Klasifikasi Data Review IMDb Berdasarkan Analisis Sentimen Menggunakan Algoritma Support Vector Machine

Authors

  • Gita Cahyani Universitas AMIKOM Yogyakarta , Yogyakarta
  • Wiwi Widayani Universitas AMIKOM Yogyakarta , Yogyakarta
  • Sharazita Dyah Anggita Universitas AMIKOM Yogyakarta , Yogyakarta
  • Yoga Pristyanto Universitas AMIKOM Yogyakarta , Yogyakarta
  • Ikmah Ikmah Universitas AMIKOM Yogyakarta , Yogyakarta
  • Acihmah Sidauruk Universitas AMIKOM Yogyakarta , Yogyakarta

DOI:

https://doi.org/10.30865/mib.v6i3.4023

Keywords:

Sentiment Analysis, Support Vector Machine, Internet Movie Database (IMDb)

Abstract

Advances in Web 2.0 technology encourage the creation of personal website content involving sentiments such as blogs, tweets, web forums, and various types of social media. The Internet Movie Database (IMDb) is a website that provides information about films from around the world, including the people involved, nominations received, and reviews from visitors. The number of movies and reviews on IMDb causes users or visitors to check the reviews to find out the film rating, so it takes time for users who have no experience using IMDb. Sentiment analysis can be a solution to label positive and negative reviews. One of the algorithms used in sentiment analysis is the Support Vector Machine (SVM) algorithm. This study aimed to test the accuracy of the SVM algorithm in the classification of sentiment review films on IMDb. The tests carried out using the Support Vector Machine algorithm resulted in an accuracy value of 86.5%. The SVM algorithm can also produce a precision value of 90.67% and a recall value of 91.62%.

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Published

2022-07-25

Issue

Vol. 6 No. 3 (2022): Juli 2022

Section

Articles

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