Prediksi Rating Game Menggunakan Algoritme C4.5 Berdasarkan Entertainment Software Rating Board
Abstract
Games can be played by all ages including children. If the game being played is not in accordance with the child's developmental period, it will have a negative impact on the child. Therefore, the rating on the game is very influential because if there is an error in rating the game, minors can play games that are not in accordance with their developmental needs. The purpose of this research is to create a machine learning model to predict game ratings using data from the ESRB (Entertainment Software Rating Board). This study uses the C4.5 classification algorithm and the python programming language. The data used in this study is game rating data taken from 2020 to 2022. The results of this study indicate that the machine learning model created can predict game ratings with a ratio of 70% training data and 30% testing data, with an accuracy rate of 86%.
Keywords: Game; Data Mining; Classification; Algorithm C4.5
Abstrak
Game dapat dimainkan oleh semua kalangan usia termasuk usia anak-anak. Jika game yang dimainkan tidak sesuai dengan masa kembang anak maka akan berdampak negatif kepada anak. Oleh sebab itu rating pada game sangat berpengaruh karena apabila terjadi kesalahan terhadap pemberian rating pada game anak dibawah umur dapat memainkan game yang tidak sesuai dengan kebutuhan tumbuh kembangnya. Tujuan penelitian ini adalah membuat model machine learning untuk memprediksi rating pada game dengan menggunakan data dari ESRB (Entertainment Software Rating Board). Penelitian ini menggunakan algoritme klasifikasi C4.5 dan bahasa pemrograman python. Data yang digunakan pada penelitian ini adalah data rating game yang diambil dari tahun 2020 sampai 2022. Hasil dari penelitian ini menunjukkan model machine learning yang dibuat dapat memprediksi rating game dengan perbandingan 70% data training dan 30% data testing, dengan tingkat akurasi sebesar 86%.
Kata kunci: Game; Data Mining; Klasifikasi; Algoritme C4.5
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