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

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 correc...

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Bibliographic Details
Main Authors: Sumin Sumin, Prihantono Prihantono, Khairawati Khairawati
Format: Article
Language:English
Published: Universitas Pattimura 2025-01-01
Series:Barekeng
Subjects:
artificial neural networks
single tuition fee
classification
random forest
Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15112
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