Article Per Year (5 Year)
p-Index From 2020 - 2025
0.925
P-Index
This Author published in this journals
All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Telematika : Jurnal Informatika dan Teknologi Informasi JAIS (Journal of Applied Intelligent System) JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia)
Rismiyati Rismiyati
Universitas Diponegoro
Computer Science & IT Education Electrical & Electronics Engineering Environmental Science Public Health Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Telematika : Jurnal Informatika dan Teknologi Informasi

 1 
VGG16 Transfer Learning Architecture for Salak Fruit Quality Classification Rismiyati Rismiyati; Ardytha Luthfiarta
Telematika Vol 18, No 1 (2021): Edisi Februari 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i1.4025

Abstract

Purpose: This study aims to differentiate the quality of salak fruit with machine learning. Salak is classified into two classes, good and bad class.Design/methodology/approach: The algorithm used in this research is transfer learning with the VGG16 architecture. Data set used in this research consist of 370 images of salak, 190 from good class and 180 from bad class. The image is preprocessed by resizing and normalizing pixel value in the image. Preprocessed images is split into 80% training data and 20% testing data. Training data is trained by using pretrained VGG16 model. The parameters that are changed during the training are epoch, momentum, and learning rate. The resulting model is then used for testing. The accuracy, precision and recall is monitored to determine the best model to classify the images.Findings/result: The highest accuracy obtained from this study is 95.83%. This accuracy is obtained by using a learning rate = 0.0001 and momentum 0.9. The precision and recall for this model is 97.2 and 94.6.Originality/value/state of the art: The use of transfer learning to classify salak which never been used before.
Co-Authors Ardytha Luthfiarta Dinar Mutiara Kusumo Nugraheni Edy Suharto Eko Adi Sarwoko Guruh Aryotejo Iffa Zainan Nisa Khadijah, Khadijah Priyo Sidik Sasongko Retno Kusumaningrum Sukmawati Nur Endah