KLASIFIKASI JENIS PASIR MATERIAL BANGUNAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) BERDASARKAN EKSTRAKSI CIRI TEKSTUR DAN WARNA

Yulia Astutik, . (2022) KLASIFIKASI JENIS PASIR MATERIAL BANGUNAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) BERDASARKAN EKSTRAKSI CIRI TEKSTUR DAN WARNA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

type of sand has a great influence on the results of construction so that we must be able to choose the type of sand that suits the needs of the building. In this study, sand type image classification will be classified using Support Vector Machine (SVM) classification method combined with Gray Level Co-Occurrence Matrix method to extract texture features and Color Moment RGB for color feature extraction. The dataset used in this research is 500 images consisting of 5 classes with the amount of data for each class is 100 image data. In the classification process, the image dataset will be divided into 80% training data and 20% testing data and then create one-vs-rest multi-class SVM classification model based on GLCM texture characteristics and Color Moment RGB colors. After the classification process is carried out, the accuracy value is 94% with an angle of 135 degrees and an image size of 250 x 250 pixels.

Item Type:	Thesis (Skripsi)
Additional Information:	[No Panggil : 1810511025] [Pembimbing 1 : Didit Widiyanto] [Pembimbing 2 : Catur Nugrahaeni P.D] [Penguji 1 : Yuni Widiastiwi] [Penguji 2 : Mayanda Mega Santoni]
Uncontrolled Keywords:	Sand types, SVM, Color Moment, GLCM
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Yulia Astutik
Date Deposited:	27 Jul 2022 05:50
Last Modified:	10 Aug 2022 06:37
URI:	http://repository.upnvj.ac.id/id/eprint/19748

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