Maghfiroh, Elsa Lutfi (2021) Penerapan Data Mining Untuk Menentukan Kualitas Produk Mentah Kelapa Sawit Menggunakan Metode Naive Bayes. Other thesis, Universitas Islam Riau.
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Abstract
As one of the largest Crude Palm Oil (CPO) and Palm Kernel Oil (PKO) producers in Asia, palm oil processing factories in Indonesia, especially PT. Sari Lembah Subur (SLS) 1 is required to produce good quality raw products. The quality of the resulting product depends on the content of the final processing. The content consists of Impurities in CPO ( Dirt CPO), Water Content in CPO ( Moisture CPO), Free Fatty Acid Levels in CPO (FFA CPO), Bleaching Power Index in CPO (DOBI CPO), Beta Carotene in CPO ( Carotene CPO). ), levels of dirt in the kernel ( dirt kernel), moisture content in the kernel ( moisture kernel), and damaged kernels (Broken Kernels). From these eight criteria, the Labor officer will then decide whether the raw products produced in a day of processing are of very good quality, good quality, medium quality, and poor quality. Determination of product quality is done by reviewing one by one and takes a long time. Therefore, a system is needed to assist officers in the final determination of the quality of raw products in order to shorten the time. One of them is by processing the data mining ( Data Mining ). Furthermore, by using the Naive Bayes algorithm , the probability or opportunity for each learning data will be calculated to obtain the highest value that leads to results in the form of information on the quality of raw products at the PKS factory. By testing using the K-fold cross validation method , this system has a high level of accuracy with a value of 80.5% to determine the best quality of crude palm oil products . From the results of the black box testing that has been carried out, each form of this system has met expectations in minimizing errors, whether it is invalid data or errors in data input .
| Item Type: | Thesis (Other) | ||||||
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| Uncontrolled Keywords: | Palm Oil, Quality, Product, Nave Bayes, Data Mining | ||||||
| Subjects: | Q Science > QA Mathematics > QA76 Computer software | ||||||
| Divisions: | > Teknik Informatika | ||||||
| Depositing User: | Febby Amelia | ||||||
| Date Deposited: | 21 May 2022 07:03 | ||||||
| Last Modified: | 21 May 2022 07:03 | ||||||
| URI: | http://repository.uir.ac.id/id/eprint/11027 |
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