Analisis Klasifikasi 7 Jenis Dry Beans dengan Penerapan Metode Naïve Bayes
DOI:
https://doi.org/10.26418/justin.v12i2.73034Keywords:
Dry Beans, Klasifikasi, Naïve BayesAbstract
Penelitian ini dimaksudkan untuk mengklasifikasikan jenis Dry Beans dengan menggunakan algoritma Naïve Bayes dengan bantuan alat analisis data RapidMiner. Dataset yang terlibat mencakup sejumlah atribut, termasuk Area, Perimeter, MajorAxisLength, MinorAxisLength, AspectRation, Eccentricity, ConvexArea, EquivDiameter, Extent, Solidity, Roundness, Compactness, ShapeFactor2, ShapeFactor3, ShapeFactor4, serta atribut target Class yang menunjukkan jenis Dry Beans. Dataset ini dibagi menjadi dua bagian: data training sebanyak 9528 data dan data uji sebanyak 4083 data. Hasil penelitian menunjukkan bahwa model klasifikasi Naïve Bayes berhasil mencapai tingkat akurasi sebesar 90.01% dalam mengklasifikasikan jenis Dry Beans. Hasil ini menandakan bahwa model tersebut memiliki kemampuan yang baik dalam membuat prediksi yang sesuai dengan data asli. Dengan demikian, analisis ini diharapkan dapat memberikan kontribusi dalam identifikasi, manajemen, dan pemanfaatan jenis-jenis Dry Beans secara efisien.
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