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All Journal Jurnal Informatika Majalah Ilmiah UNIKOM Jurnal Teknologi dan Informasi
Tono Hartono
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Arts Humanities Computer Science & IT Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Jurnal Informatika

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Hyper Parameter Tuning of Multilayer Convolutional Network and Augmentation Method for Classification Motive of Batik Agus Nursikuwagus; tono hartono; M A Nurwicaksono; M M Choir; M A Saputri
Jurnal Informatika Vol 17, No 1 (2023): January 2023
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v17i1.a25823

Abstract

The purpose of this research is to create a batik motive image classification system to make it easier for the public to know the name of a type of batik motive. In carrying out this research, a quantitative method was used with seven kinds of batik motives that were augmented first, where 70% of the dataset was used for training and 30% for testing so that the accuracy and precision of the system were obtained. The result of this research is that the accuracy and precision of the system in classifying batik motive images is 0.985 or 98.5%. This high accuracy and precision were obtained because the quality of the previous dataset was improved by augmenting geometric and photometric. The machine learning method used was a Convolutional Neural Network which in previous studies also provided the highest accuracy and precision. The results of this study can be used for various purposes such as marketing, cultural reservation, and science.
Co-Authors Agus Nursikuwagus Iyan Gustiana M A Nurwicaksono M A Saputri M M Choir Mohamad Indra Firmansyah Novrini Hasti wahyuni wahyuni