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Zulfahmi Zulfahmi
Computer Systems, Universitas Pembangunan Pancabudi Medan
Computer Science & IT

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APPLICATION OF K-NEAREST NEIGHBOR METHOD IN CLASSIFICING THE RATE OF PAPAYA MURABILITY BASED ON FRUIT COLOR FORM Danu Wardhana Azhari; Zulham Sitorus; Zulfahmi Zulfahmi
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

Papaya is a type of nutrient-rich fruit that offers many health benefits. The highest nutritional content in papaya is vitamin A. Papaya is also a climbing fruit that is usually harvested and distributed. In an immature state with different degrees of aging. The high public awareness of the importance of consumption of papaya fruit affects the increase in demand for papaya fruit and therefore supply. The K-NN algorithm produces an accuracy rate of 75% and error 25% with 3 attributes, 3 classes and 18 data for classifying. The results of the model carried out are quite good by looking at the resulting accuracy value, although it is not 100% perfect. The author hopes that further research will apply the same parameters to avoid missing values in pre-processing data. It is hoped that further research will be developed by applying this classification model with other and larger data
Co-Authors Danu Wardhana Azhari Sitorus, Zulham