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Julianto, Faiza Muhammad
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Computer Science & IT Engineering

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Penerapan Model Regresi Linear Untuk Memprediksi Overall Rating Kiper (GK) Dalam EA FC 25 Julianto, Faiza Muhammad; Tawakal, Iqbal; Mu'minin, Amirul; Anam, Misbakhul
Journal of Practical Computer Science Vol. 4 No. 2 (2024): November 2024
Publisher : DPPM Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/jpcs.v4i2.6070

Abstract

Player performance prediction in digital soccer games is a growing research topic, especially in supporting data-driven evaluation. In this study, the Overall Rating (OVR) of Goalkeeper (GK) players in EA FC 25 game is predicted using Linear Regression model. The main objective of this study is to evaluate the model's ability to predict OVR based on goalkeeper-specific attributes. The methodology used includes data collection, pre-processing, feature selection, model building, and model performance evaluation using Root Mean Squared Error (RMSE), R-squared (R²), and Mean Absolute Error (MAE) metrics. The evaluation results show that the model has an R-squared value of 0.99, RMSE of 0.72 and MAE of 0.57, indicating that the model is able to provide predictions with low error and high accuracy. These findings suggest that linear regression is effective in modeling the relationship between goalkeeper attributes and Overall Rating scores in the context of EA FC 25 game
Co-Authors Anam, Misbakhul Iqbal Tawakal, Iqbal Mu'minin, Amirul