Optimizing Random Forest Parameters with Hyperparameter Tuning for Classifying School-Age KIP Eligibility in West Java

Optimizing Random Forest Parameters with Hyperparameter Tuning for Classifying School-Age KIP Eligibility in West Java

Random Forest is an ensemble learning algorithm that combines multiple decision trees to generate a more stable and accurate classification model. This study aims to optimize Random Forest parameters for classifying school-age students' eligibility for the Kartu Indonesia Pintar (KIP) in West J...

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Bibliographic Details
Main Authors: Silfiana Lis Setyowati, Asyifah Qalbi, Rafika Aristawidya, Bagus Sartono, Aulia Rizki Firdawanti
Format: Article
Language:English
Published: Department of Mathematics, Universitas Negeri Gorontalo 2025-02-01
Series:Jambura Journal of Mathematics
Subjects:
kartu indonesia pintar (kip)
random forest
smote
optimal parameter
hyperparameter tuning
Online Access:https://ejurnal.ung.ac.id/index.php/jjom/article/view/28736
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