Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal Teknologi
Ismi Amalia
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
IDENTIFIKASI JENIS KAYU BERBASIS CITRA MENGGUNAKAN PROBABILISTIC NEURAL NETWORK (PNN) Ismi Amalia
Jurnal Teknologi Vol 14, No 2 (2014): Jurnal Teknologi
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v14i2.248

Abstract

The purpose of this research is to identify the types of wood based on imagery by using PNN method. In this paper, gray level co-occurence matrix (GLCM) is used as texture classification techniques. The GLCMs are generated to obtain three features: autocorrelation, cluster shade and sum variance. The classification technique used to classify the wood species is a probabilistic neural network (PNN). This research was carried out using 12 different types of wood. For each type of wood, 6 images were collected. The images of wood were divided in two sets: training set and test set. The leave-one-out cross-validation technique was applied for model validation. Our experimental results showed that the proposed method can increase the recognition rate up to 80.55%. The result of this research indicated that three features of GLCM are accurate to distinguish types of wood. This research used only a small-size dataset, so for further research is needed to use more feature extract methods and types of wood
Co-Authors