Jurnal Teknologi Informasi dan Terapan (J-TIT)
Vol 2 No 1 (2015)

ANALISIS FITUR TEKSTUR DAUN MANGGA DENGAN FISHER’S DISCRIMINANT RATIO UNTUK PENCAPAIAN FITUR YANG INFORMATIF

Eko Prasetyo (Universitas Bhayangkara Surabaya)



Article Info

Publish Date
09 Mar 2019

Abstract

Mango tree species recognition system based on the texture of leaves on the previous system gives accuracy up to 88.89%. This indicates that feature selection of research on the mango tree species recognition need to be taken into account. In this research, analysis of mango leaf texture features are used. There are 3 types of features that is: statistics, invariant moment, and the co- occurrence matrix. Methods for analyzing the feature is Fisher's Discriminant Ration (FDR). This method obtained from a number of informative features, that is: energy (co-occurrence), uniformity (statistics), the third moment (statistics), entropy (co-occurrence), entropy (statistical), and homogeneity (co-occurrence). Performance testing is done by comparing the use of old and new features on the K-Nearest Neighbor method with the value K is 3, 5, 7, and 11. The results showed that the accuracy of the K-NN method with new features reach 0.90, and tend to be better than the old features.

Copyrights © 2019






Journal Info

Abbrev

jtit

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

This journal accepts articles in the fields of information technology and its applications, including machine learning, decision support systems, expert systems, data mining, embedded systems, computer networks and security, internet of things, artificial intelligence, ubiquitous computing, wireless ...