Browsing by Author "Ikhlas, Ariza"

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    MESIN PEMBELAJARAN ENSEMBLE UNTUK IDENTIFIKASI VARIETAS PADI
    (Sekretariat Badan Penelitian dan Pengembangan Pertanian, ) Ikhlas, Ariza; Abdullah, Abdullah; Universitas Islam Indragiri; Prasetyo, Dwi Yuli
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    MESIN PEMBELAJARAN ENSEMBLE UNTUK IDENTIFIKASI VARIETAS PADI
    (Sekretariat Badan Penelitian dan Pengembangan Pertanian, 2020-06-15) Ikhlas, Ariza; Abdullah; Prasetyo, Dwi Yuli
    Each rice variety has certain characteristics with different planting recommendations. Farmers generally find it difficult to select rice varieties suitable for planting on their land due to a lack of identification capabilities. The classification algorithm is a solution to this problem because it is able to identify rice varieties through digital images. The purpose of this study was to apply and evaluate several classification algorithms to identify rice varieties using color and texture features. The research was conducted in Indagiri Hilir Riau district in 2018. Machine learning was built by combining several classification algorithms (classifier), namely Support Vector Machine, k-Nearest Neighbors, Logistic Regression, and Decision Tree. The varietes studied were varieties IR42, Inpara-9. and Batang Piaman. Based on the level of accuracy of each algorithm, k-Nearest Neighbors gives better results than other algorithms, both with and without normalization data. There were six samples of Inpara-9 that were predicted to be true (true positive) and five samples were redicted to be false (false positive). In the Batang Piaman, there were eight samples that were predicted to be true (true positive). In IR42, there were five samples that were predicted to be true.