Please use this identifier to cite or link to this item: http://repository.kalbis.ac.id/handle/123456789/449
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dc.contributor.authorRusli, Hizkia Natanael-
dc.contributor.advisorPrabowo, Yulius Denny-
dc.date.accessioned2022-08-23T09:46:35Z-
dc.date.available2022-08-23T09:46:35Z-
dc.date.issued2022-08-12-
dc.identifier.urihttp://repository.kalbis.ac.id/handle/123456789/449-
dc.description.abstractThis study aims to develop an image classification application for the ripeness level of apples using the Convolutional Neural Network method to group image data so that it can assist in determining the ripeness of apples. The dataset used is an image of unripe, ripe, and rotten apples. The data will be trained to obtain accuracy to determine the level of ripeness of apples. In this study, the accuracy was 96% for 20 epochs and 98% for 40 epochs.en_US
dc.language.isootheren_US
dc.publisherInstitut Teknologi dan Bisnis Kalbisen_US
dc.subjectMachine Learningen_US
dc.subjectCNNen_US
dc.subjectTensorflowen_US
dc.subjectKerasen_US
dc.titlePengembangan Aplikasi Klasifikasi Tingkat Kematangan Buah Apel Berdasarkan Warna Kulit Buah Apel dengan Metode Convolutional Neural Networken_US
dc.typeThesisen_US
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