IMPROVING CLUSTER ACCURACY IN TUITION FEES: A MULTILAYER PERCEPTRON NEURAL NETWORK AND RANDOM FOREST APPROACH

Manual classification of Single Tuition Fees (STF) has a high risk of misclassification due to the need for a more in-depth assessment of students' economic criteria. This research uses Artificial Neural Networks (ANN), specifically the Multilayer Perceptron (NN-MLP) model, to detect and correct err...

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Autores principales:	Sumin Sumin, Prihantono Prihantono, Khairawati Khairawati
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Universitas Pattimura 2025-01-01
Colección:	Barekeng
Materias:	artificial neural networks single tuition fee classification random forest
Acceso en línea:	https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15112
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