Performance Comparative Study of Machine Learning Classification Algorithms for Food Insecurity Experience by Households in West Java

Performance Comparative Study of Machine Learning Classification Algorithms for Food Insecurity Experience by Households in West Java

This study aims to compare the classification performance of the random forest, gradient boosting, rotation forest, and extremely randomized tree methods in classifying the food insecurity experience scale in West Java. The dataset used in this research is based on the Socio-Economic Survey by Stati...

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Bibliographic Details
Main Authors: Khusnia Nurul Khikmah, Bagus Sartono, Budi Susetyo, Gerry Alfa Dito
Format: Article
Language:English
Published: Department of Informatics, UIN Sunan Gunung Djati Bandung 2024-06-01
Series:JOIN: Jurnal Online Informatika
Subjects:
extremely randomized tree
food insecurity
gradient boosting
random forest
rotation forest
Online Access:https://join.if.uinsgd.ac.id/index.php/join/article/view/1012
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