Please use this identifier to cite or link to this item: http://repository.kalbis.ac.id/handle/123456789/467
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPratama, Yogie Eka-
dc.contributor.advisorPrabowo, Yulius Denny-
dc.date.accessioned2022-08-24T05:45:31Z-
dc.date.available2022-08-24T05:45:31Z-
dc.date.issued2022-08-22-
dc.identifier.urihttp://repository.kalbis.ac.id/handle/123456789/467-
dc.description.abstractThis study has one goal, namely to be able to identify the similarity of paintings through painting imagery and from the image of the painting that has been input will show which artist's work is supposedly similar to the image that has been input. The algorithm used is a Convolutional Neural Network (CNN). This study used painting imagery data from Kaggle in the form of a folder. The image data used was 4299 which was divided into training data and testing data with a total of 3444 data from 11 classes and testing data as many as 855 from 11 classes. The framework used in this study is ResNet-50 and the Convolutional Neural Network which is applied is Tensorflow Keras. The results of the study, it has produced an accuracy value of 24% with an average probability of up to about 80% and above.en_US
dc.language.isootheren_US
dc.publisherInstitut Teknologi dan Bisnis Kalbisen_US
dc.subjectPainting imageen_US
dc.subjectAccuracyen_US
dc.subjectConvolutional Neural Networken_US
dc.subjectTrainingen_US
dc.subjectTestingen_US
dc.subjectResNet50en_US
dc.titlePengembangan Aplikasi Pembelajaran Mesin untuk Identifikasi Kemiripan Lukisanen_US
dc.typeThesisen_US
Appears in Collections:IF 2022

Files in This Item:
File Description SizeFormat 
A_Cover_2018104043.pdfCover307.66 kBAdobe PDFView/Open
B_Abstrak_2018104043.pdfAbstrak207.77 kBAdobe PDFView/Open
C_Daftar_isi_2018104043.pdfDaftar isi221.26 kBAdobe PDFView/Open
D_Bab1_2018104043.pdfBab 1286.09 kBAdobe PDFView/Open
E_Bab2_2018104043.pdf
  Restricted Access
Bab 21.25 MBAdobe PDFView/Open Request a copy
F_Bab3_2018104043.pdf
  Restricted Access
Bab 31.02 MBAdobe PDFView/Open Request a copy
G_Bab4_2018104043.pdf
  Restricted Access
Bab 4615.34 kBAdobe PDFView/Open Request a copy
H_Bab5_2018104043.pdf
  Restricted Access
Bab 5138.8 kBAdobe PDFView/Open Request a copy
I_Daftar_pustaka_2018104043.pdfDaftar pustaka341.99 kBAdobe PDFView/Open
J_Full_Text_2018104043.pdf
  Restricted Access
Full text2.77 MBAdobe PDFView/Open Request a copy
Certificate_of_approval_2018104043.pdf
  Restricted Access
Certificate of approval97.83 kBAdobe PDFView/Open Request a copy
Plagiasi_2018104043.pdf
  Restricted Access
Plagiasi18.22 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.