IMPLEMENTASI KUALITAS MINUMAN WINE MENGGUNAKAN METODE KLASIFIKASI
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Abstract
This study aims to evaluate wine quality using three different classification algorithms: K-Nearest Neighbor (KNN), Artificial Neural Network (ANN), and Polynomial regression. The data used in this study comes from the Wine Quality repository, which includes various chemical attributes of wine, such as alcohol content, acidity, and sugar. Each algorithm is evaluated based on several performance metrics, including precision, recall, f1-score, and accuracy.
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This work is licensed under a Jurnal Komunikasi Creative Commons Attribution-ShareAlike 4.0 International License.
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