Quality Classification of Palm Oil Products Using Naïve Bayes Method

Des Suryani, Ana Yulianti, Elsa Lutfi Maghfiroh, Jepri Alber

Abstract


Indonesia is a country that can produce the highest palm oil in the world. The islands of Sumatra and Kalimantan are the islands that have the largest plantations, especially oil palm in Indonesia. Riau Province which is located on the island of Sumatra can produce the highest oil palm on the island of Sumatra. Quality is an important component in business continuity in the palm oil industry. The quality of the crude palm oil products of a company in the Kerumutan sub-district, Pelalawan district, Riau, depends on the content of the final processing product. The content consists of impurities in crude palm oil (CPO), CPO moisture content, free fatty acid CPO levels, determination of bleachability index CPO, CPO carotene, dirt kernel, moisture kernel, and broken kernel. The final quality of palm oil products is determined from the combined results of CPO quality and kernel quality. Good quality raw materials will affect the selling price of these raw materials to produce a good quality final product. Determine the quality of palm oil products poses a problem in terms of time because they must be checked one by one through processing in the laboratory. Application builder who can determine the quality classification of palm oil products is the purpose of this research. This application is expected to help labor officers in the process of classifying the quality of crude palm oil products more quickly, precisely, and accurately. This study uses the Naïve Bayes algorithm because it requires smaller amounts of training data in the data classification process. The accuracy level of the Naïve Bayes method in determining the quality of palm oil products is 82.05%.


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DOI: https://doi.org/10.32520/stmsi.v11i1.1713

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