Analisis Perbandingan Algoritma Random Forest dan Support Vector Machine untuk Klasifikasi Hasil Pertandingan Tim Sepak Bola Liga Utama Inggris Musim 2022/2023

Abstract

Football is not only about the passes and shots that must be taken into account in the course of a game, but also about the composition and strategy that each team must have in order to maximize each game and win. Therefore, a classification is needed to identify the factors that influence the team's victory in a football match. One approach that can be done is to use existing algorithms in machine learning, namely the Random Forest Algorithm and the Support Vector Machine Algorithm, which can identify and classify the results of football matches and provide additional information for clubs to design game strategies in facing other clubs so that they are effective in each match. The results of the system tests show that the Random Forest algorithm achieved an overall accuracy value of 94%. Meanwhile, the Support Vector Machine algorithm using multiple kernels, namely the linear, radial, and polynomial kernels, obtained a total accuracy value of 100%, 88%, and 97%, respectively. This shows that the Support Vector Machine (SVM) classification is excellent.