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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Abdullah Hamid
STMIK KAPUTAMA
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Measuring the Maturity Level of Oil Palm Fruit For CPO Production Based on Color With Using the LVQ Method Abdullah Hamid; Rusmin Saragih; Siswan Syahputra
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.303

Abstract

Palm oil is a very important commodity besides oil and gas which also has a fairly good export value. The palm oil produced must be supported by the quality standards set by SNI. The level of maturity when harvesting oil palm fruit greatly influences the quality of Crude Palm Oil (CPO) production, which is crude palm oil that has a reddish color obtained from extraction or from the pressing process of oil palm fruit flesh. In fact, in the field of oil palm fruit harvest, there are still many oil palm fruit that are not ripe enough and can even be said to be still raw, entering the CPO production process. Determination of the maturity level of oil palm fruit is generally determined based on the amount of loose fruit and color, so handling the harvest of oil palm fruit is an important activity in improving the quality of CPO. It is necessary to build a system capable of managing and processing palm fruit images to measure the maturity level of the palm fruit to be produced. To obtain the right level of accuracy, this research uses the Learning Vector Quantization (LVQ) method. LVQ is a method for conducting supervised competitive layer learning. From the results of trials conducted, it is proven that the system can measure very ripe oil palm fruit with HSV values (0.052209; 0.896021; 0.791114).
Co-Authors Rusmin Saragih, Rusmin Siswan Syahputra