Support vector machine with a firefly optimization algorithm for classification of apple fruit disease

Wikky Fawwaz Al Maki; Amien Jafar Makrufi

doi:10.30812/matrik.v22i1.2365

Wikky Fawwaz Al Maki Universitas Telkom
Amien Jafar Makrufi Universitas Telkom

DOI: https://doi.org/10.30812/matrik.v22i1.2365

Keywords: Apple Disease, Classification, Support Vector Machine, Firefly Algorithm

Abstract

Fruit diseases became one of the serious problems that the farmer faced because it could threaten their economic outcome. The main focus of this study is apples. Apple fruit is very susceptible to disease, in general diseases that usually attack the apple are blotch apple, rot apple, and scab apple. In this study, the author is classifying these three apple diseases and normal apples. Classification is a process that we can do manually by human power, which costs a lot of fortune, takes a long time, and it's also very vulnerable to false identification. This study takes advantage of computer vision technology and machine learning to overcome the classification problem. By using the SVM method and parameter FA optimization algorithm, we can get the highest result only in the first experiment and also with 94% accuracy.

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