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Copyright (c) 2022 Digital Zone: Jurnal Teknologi Informasi dan Komunikasi

Quality Classification of Palm Oil Varieties Using Naive Bayes Classifier

As one of the leading commodities of the Indonesian economy, the ever-increasing production of palm oil has created intense competition among palm oil (CPO) producers. This causes CPO producers to increase their palm oil production without compromising the quality of the palm oil produced. CPO producers are required to be able to objectively determine the quality of superior and precise oil palm varieties in order to produce high economic value palm oil. Therefore, a model is needed to determine the quality of oil palm from several existing varieties. The Naive Bayes Classifier method in this study was used to classify the quality of oil palm based on predetermined variables using a data set of 28 oil palm varieties. Method testing is done by using a confusion matrix and K-fold cross-validation scheme. This study shows a reasonably high accuracy value of 64.25% and a low error rate of 35.7%, indicating that the Naive Bayes Classifier can classify the quality of oil palm varieties quite well. 

Informasi Detail
Journal
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi; Vol. 13 No. 1 (2022): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi ; 11-23
Penerbit
Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning
Tahun Terbit
Bahasa
eng
ISSN
-
License
Copyright (c) 2022 Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Last Updated
2023-12-19T03:54:45Z
Info Journal

Digital Zone: Jurnal Teknologi Informasi dan Komunikasi; Vol. 13 No. 1 (2022): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi ; 11-23

Penerbit: Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning