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 : JAIS (Journal of Applied Intelligent System)

 1 
Transfer Learning with Xception Architecture for Snakefruit Quality Classification Rismiyati Rismiyati; Ardytha Luthfiarta
Journal of Applied Intelligent System Vol 7, No 2 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i2.6797

Abstract

Machine learning has been greatly used in the field of image classification. Several machine learning techniques perform very well in this task. The development of machine learning technique in recent years are in the direction of deep learning. One of the main challenge of deep learning is that it requires the number of the samples to be extremely large for the model to perform well. This is because the number of feature that trainable parameter are huge. One of the solution to overcome this is by introducing transfer learning. One of the architecture that is currently introduced is Xception architecture. This architecture is claimed to outperform VGG16, ResNet50, and inception in terms of model accuracy and model size. This research aims to classify snakefruit quality by using transfer learning with Xception architecture. This is to explore possibility to achieve better result as Xception architecture generally perform better than other available architecture in transfer learning. The snakefruit quality is classified into two classes. Hyperparameter value is optimized by several scenario to determine the best model. The best performance is achieved by using learning rate of 0.0005, momentum 0.9 and dropout value of 0 or 0.25. The accuracy achieved is 94.44%.
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