JOINT (Journal of Information Technology
Vol 1 No 1 (2019): JoinT (Journal of Information Technology)

Metode Grayscale Co-occurrence Matrix (GLCM) Untuk Klasifikasi Jenis Daun Jambu Air Menggunakan Algoritma Neural Network

Suhendri Suhendri (STMIK "AMIKBANDUNG")
Putri Rahayu (STMIK "AMIKBANDUNG")



Article Info

Publish Date
19 Feb 2019

Abstract

The color and shape of leaves each different plant water rose so that it can be found a certain texture to classify. This study uses an image texture recognition leaves to be classified. Leaves used are three types of guava leaves, Bunton 3 Green Guava, Guava and Guava image Bol. Feature extraction process used a method is Gray Level Co-Occurrence Matrix (GLCM) with Matlab tool. GLCM is used to retrieve the value of the image attribute or value matrix. This study uses a Neural Network algorithm with a tool RapidMiner. One alternative solution to the above problems is by way of classifying types of guava leaf water by looking at the characteristics of the water guava leaves. Leaf is one of the characteristics of the plant that is easily recognizable. The classification process is to produce a good accuracy value against bunton guava leaves 3 green, pink bol, and guava image. The results showed that the level of accuracy in the guava leaf bol is 81.25%, bunton leaves 3 Green 75%, and 80% leaf image and the total value of the overall accuracy of 78.89%. Thus the above results show that the value of the accuracy of the resulting research shows three types of guava leaf water has been classified and deserves to be investigated.

Copyrights © 2019






Journal Info

Abbrev

joint

Publisher

Subject

Computer Science & IT

Description

JOINT merupakan jurnal peer-reviewed yang diterbitkan oleh Lembaga Penelitian, Pengabdian Masyarakat, dan Modal Intelektual STMIK "AMIKBANDUNG". JOINT memiliki tujuan untuk menyebarkan hasil karya ilmiah yang dihasilkan oleh dosen, peneliti, atau mahasiswa dari seluruh Indonesia agar dapat ...