Klasifikasi Jenis Buah Nanas Menggunakan Convolution Neural Network

Jodhy Dwi Marfianto, Mutaqin Akbar

Abstract


Indonesia is one of the countries with gread agricultural potential. One of the products of agriculture in Indonesia is pineapple. Pineapple is a tropical plant with edible fruit and one of the maximum economically vital plants in the Bromeliaceous family. The process of selecting pineapple species is generally very dependent on human perception. The development of technology and science makes it possible to perform classification or in terms of object selection using technology based on digital image-based characteristics. Images are used as a source of information that can be used to classify objects. One of the deep learning methods used is Convolutional Neural Networks (CNN) because they have a high deep network and are widely used to image data. Deep learning in Computer Vision has good capabilities in, one of which is image classification or object classification in images, and the network in CNN has a special layer, namely the convolution layer, The image convolution process in this study uses the keras package on GoogleColab, because making a neural network model using Keras does not need to write code to express mathematical calculations individually. Testing using a sample of 120 pineapple images shows an accuracy rate of 91,66% which is considered to be able to identify 3 types of pineapple fruit.

Keywords


Convolutional Neural Network; Klasifikasi; Nanas

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DOI: http://dx.doi.org/10.26623/transformatika.v21i2.6369

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