Inovasi Naive Bayes Classifier dalam Prediksi Rating Game untuk Pengalaman Gaming yang Lebih Menarik

Authors

  • Febri Liantoni Universitas Sebelas Maret http://orcid.org/0000-0003-1084-965X
  • Dini Erlinawati Universitas Sebelas Maret
  • Yuliana Rizki Ikhsanty Universitas Sebelas Maret
  • Fadil Indra Sanjaya Universitas Teknologi Yogyakarta
  • Mulia Sulistiyono Universitas Amikom Yogyakarta

DOI:

https://doi.org/10.26418/justin.v11i3.67228

Keywords:

Classification, Games, Naïve Bayes

Abstract

Ada beberapa jenis game yang muncul dan dibuat untuk menarik perhatian para gamers. Beberapa permainan mampu mengobati rasa lelah, panik, sedih, bosan, dan kebanyakan mengisi waktu luang. Penelitian ini bertujuan untuk mengembangkan dan menerapkan metode Naive Bayes Classifier yang inovatif dalam prediksi rating game. Dengan menggunakan pendekatan yang memberikan rekomendasi rating yang akurat untuk setiap permainan yang akan dirilis, dengan tujuan meningkatkan pengalaman gaming pengguna. Dataset yang digunakan dalam penelitian ini mencakup informasi tentang game-game yang telah dirilis sebelumnya, termasuk rating yang diberikan oleh para pengguna. Hasil eksperimen menunjukkan bahwa metode Naive Bayes Classifier yang dikembangkan kami memiliki kinerja yang baik dalam memprediksi rating game. Penelitian ini memiliki potensi untuk meningkatkan pengalaman gaming pengguna dengan memberikan rekomendasi rating yang akurat. Dengan menggunakan metode Naive Bayes Classifier yang inovatif diharapkan dapat membantu pengguna dalam membuat keputusan yang tepat tentang permainan yang akan mereka mainkan.

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Published

2023-07-31

Issue

Vol. 11 No. 3 (2023)

Section

Articles

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