Comparative Analysis of Random Forest and Support Vector Machine for Sundanese Dialect Classification Using Speech Recognition Features

Comparative Analysis of Random Forest and Support Vector Machine for Sundanese Dialect Classification Using Speech Recognition Features

This study investigates the classification of West and South Sundanese dialects using Random Forest (RF) and Support Vector Machine (SVM). Using a dataset of 100 recordings with features extracted via Mel Frequency Cepstral Coefficient (MFCC), models were evaluated by accuracy, precision, recall, an...

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Bibliographic Details
Main Authors: Abdull Halim Anshor, Tri Ngudi Wiyatno
Format: Article
Language:English
Published: LPPM ISB Atma Luhur 2025-05-01
Series:Jurnal Sisfokom
Subjects:
classification of sundanese dialects
machine learning
random forest
support vector machine
mel-frequency cepstral coefficient
Online Access:https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2347
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https://jurnal.atmaluhur.ac.id/index.php/sisfokom/article/view/2347

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