Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Indonesian Journal of Artificial Intelligence and Data Mining
Nasution, Riski Abdul Hakim
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Classification of Football Players' Abilities Using The Naïve Baiyes Method Nasution, Riski Abdul Hakim; Ikhsan, Muhammad
Indonesian Journal of Artificial Intelligence and Data Mining Vol 7, No 2 (2024): September 2024
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v7i2.31997

Abstract

This study aims to classify the abilities of football players in the BRI Liga 1 Indonesia season 2023/2024 using the Naïve Bayes method. The player data used includes individual stats such as the number of goals, assists, passing accuracy, tackles, and overall performance in the match. The Naïve Bayes method was chosen because of its efficient ability to process data with independent features. In this study, players were classified into several ability categories, such as excellent, good, adequate, and poor, based on their performance during the current season. The results of this classification are expected to provide useful information for coaches and club management in determining strategies and player development. The study also provides insight into the key factors that affect a player's performance in the league. Model testing shows that Naïve Bayes' method has an adequate level of accuracy for the classification of football players' abilities in BRI Liga 1. The practical implications of this study are increased efficiency in the process of evaluating players and making strategic decisions in professional football teams.
Co-Authors Muhammad Ikhsan