PENERAPAN METODE SUPPORT VECTOR MACHINE (SVM) PADA KLASIFIKASI JENIS CENGKEH BERDASARKAN FITUR TEKSTUR DAUN
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The Support Vector Machine (SVM) classification algorithm processes extracted feature values and accurately class leaves. This study achieves the highest accuracy of 56.67% on an image size of 250x250 pixels and 48.33% on an image size of 150x150 pixels using 150 training data and 60 test data. These results indicate the potential of automatic leaf classification in efficiently identifying clove plant species.
Keywords : Clove, Leaf, Processing, Texture, SVM
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Talib, Sadri; Sudin, Sakina; Dzikrullah Suratin, Muhammad, "PENERAPAN METODE SUPPORT VECTOR MACHINE (SVM) PADA KLASIFIKASI JENIS CENGKEH BERDASARKAN FITUR TEKSTUR DAUN," Jurnal Riset Sistem dan Teknologi Informasi, vol. 2, no. 1, Feb. 2024.
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