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Modifikasi Algoritma K-nearest Neighbour Menggunakan Chebyshev Distance Berdasarkan Gray Level Co-occurrence Matrix Untuk Klasifikasi Kayu
| Content Provider | Semantic Scholar |
|---|---|
| Author | Informatika, Jurusan Tehnik |
| Copyright Year | 2015 |
| Abstract | Indonesia is a tropical country with many types of wood. Wood is the main ingredient in the manufacture of furniture. Jepara is district that is famous for the carving in furniture. Some wood commonly used in Jepara are teak, mahogany, Mindi and Sengon. During this time the classification of wood still involves a grader. Limitedness of a grader as human beings is a grader can sometimes make mistakes when the condition is not good, or under certain conditions. In this paper examines how to classification the wood image using algorithm with the k-nearest neighbor distance calculation Chebyshev distance based on texture features gray level co-occurrence . Image data that is used is a grayscale image, both as training data and test data, and then extracted using GLCM, then the classes using KNN algorithm was modified using Chebyshev distance. The Results of study using the 400 wooden image consists of 360 training data and test data 40 with 4 classes. The research produces an accuracy of 77.5%. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://eprints.dinus.ac.id/17057/1/jurnal_16365.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
