FFB, Android, RGB, K-NN Application to detect Maturity of Palm Oil's Fresh Fruit Bunches (FFB) Based on Color Composition using K-NN algorithm
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How to Cite

Rifqi, M., Akbar, M., & Fitrisia, Y. (2020). FFB, Android, RGB, K-NN Application to detect Maturity of Palm Oil’s Fresh Fruit Bunches (FFB) Based on Color Composition using K-NN algorithm. Jurnal Komputer Terapan , 6(1), 99 - 108. https://doi.org/10.35143/jkt.v6i1.3338

Abstract

Maturation process of Fresh Fruit Bunches (FFB) palm oil can see by the changes of the skin color. Only FFB’s worth to processed that will be carried by truck to the factory. However, for this time FFB’s raw still carried to the factory. The result of this research is a web base application that organize by admin to organize data training and an android based application that can predict which FFB’s worth carrying or not to factory. The farmer just needs to take a picture of FFB’s, then the application will predict the label. The prediction result obtained is FFB’s worth to carried or not. The feature extraction that used is RGB color, then the numeric value that gotten will processed using algorithm. The algorithm that is used is k-nearest neighbor. Based on the test performed, application has reach the accuration 85% with K value = 7.
https://doi.org/10.35143/jkt.v6i1.3338
PDF (Bahasa Indonesia)
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