GDL

Journal from gdlhub / 2018-06-02 10:40:27
Oleh : Miftahus Sholihin, Siti Mujilahwati, Retno Wardhani, Kursor
Dibuat : 2018-06-02, dengan 1 file

Keyword : Batik, Classification, Preprocessing, Feature Extraction, Gray Level Cooccurence Matrix, K-Nearest Neighbors
Url : http://kursorjournal.org/index.php/kursor/article/view/114
Sumber pengambilan dokumen : WEB

Classification aims to classify object into specific classes based on the value of the attribute associated with the object being observed. In this research designed a system that serves to classify Lamongan batik cloth based on color features using color moment, texture using Gray Level Co-occurence Matrix (GLCM), and shape using moment invariant, classification using K-Nearest Neighbors (K-NN) method. In outline the system was built consists of three main processes namely pre-processing, feature extraction, and classification. The highest accuracy rate in this study was 90.4% when the value of k = 6.

Beri Komentar ?#(0) | Bookmark

Properti	Nilai Properti
ID Publisher	gdlhub
Organisasi	Kursor
Nama Kontak	Herti Yani, S.Kom
Alamat	Jln. Jenderal Sudirman
Kota	Jambi
Daerah	Jambi
Negara	Indonesia
Telepon	0741-35095
Fax	0741-35093
E-mail Administrator	elibrarystikom@gmail.com
E-mail CKO	elibrarystikom@gmail.com