TEKNOLOGI NON DESTRUKTIF DAN MACHINE LEARNING UNTUK PREDIKSI KUALITAS BUAH: TINJAUAN LITERATUR 2015-2020

Ali Khumaidi

doi:10.21107/agrointek.v15i1.7810

TEKNOLOGI NON DESTRUKTIF DAN MACHINE LEARNING UNTUK PREDIKSI KUALITAS BUAH: TINJAUAN LITERATUR 2015-2020

Ali Khumaidi

Abstract

Accuracy in the prediction of fruit quality is very important to provide the best products to consumers and increase economic value. To produce accurate prediction of good fruit quality, it is needed the right technological instruments and data processing techniques. In this literature review systematically summarizes and analyzes non-destructive technology and machine learning for the prediction of fruit quality over the past 5 years and its challenges and explores future opportunities and prospects for forming the latest references for researchers. Based on the results of the analysis that for accuracy and speed in the examination of fruit quality for internal and external attributes required different technological approaches, methods and algorithms according to their characteristics. Development of technology and algorithms continues to be achieved to achieve the goal that is the presence of fruit quality detection devices that are fast, reliable, portable, and cost-effective.

Keywords

Fruit Quality, Machine Learning, Non Destructive, Prediction, Technology

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