SELEKSI FITUR FORWARD SELECTION PADA ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI BENIH GANDUM

Femi Dwi Astuti

Sari


Abstract - Wheat (Triticum aestivum L) is one of the staple food ingredients besides rice. The demand for the wheat in the world until 2020 is estimated to increase by 1.6% per year. The data processing for wheat seeds has been done a lot, one of them is by using data mining classification techniques. The feature selection is used before the classification process to optimize the accuracy values from the classification results. The feature selection used in this research is forwarding the selection which is applied to the Naive Bayes algorithm to classify the wheat seeds.

The results of this study indicate that the value of the accuracy and the wheat classification  after using the feature selection has a higher value of 93.81% compared to the condition before using the feature selection of 90.48%. The precision results also increased from 91.49% to 94.81%.

 Keywords: Forward Selection, Naive Bayes, Classification, Gandum.


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Referensi


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