Pengelompokan Buah Jeruk menggunakan Naïve Bayes dan Gray Level Co-occurrence Matrix


Rahmat Karim Haba(1*); Kartika Chandra Pelangi(2);

(1) Universitas Ichsan Gorontalo
(2) Universitas Ichsan Gorontalo
(*) Corresponding Author

  

Abstract


Tangerines are fruits that are rich in high vitamin C content. Every orchard owner always tries to improve the quality of their plantation. In the selection of tangerines to be classified as ripe or immature at harvest time, the garden planters are already accustomed, but sometimes the farmer grouping the ripe oranges has problems such as physical limitations of the farmer, which is caused by fatigue factor. because it is still grouping with conventional systems so it is not effective and efficient in classifying ripe oranges. So from that we need a computerized system that can help gardeners in classifying ripe oranges. One of the technologies currently developing in agriculture and plantations is digital image processing using a classification system based on the texture and naïve bayes method. Based on the results that have been made, that the classification system using the Naïve Bayes method on tangerine images can be classified and obtain effective and efficient performance based on testing of 82% so that it can be implemented.


Keywords


Classification; GlCM; Naïve Bayes

  
  

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doi  https://doi.org/10.33096/ilkom.v12i1.494.17-24
  

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