Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Innovation in Research of Informatics (INNOVATICS)
Yunianti, Rizqi
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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

Found 1 Documents
Search

 1 
Classification Of The Maturity Level Of Glutinous Rice Tape Fermentation Using Convolutional Neural Network Yunianti, Rizqi; Murinto, Murinto
Innovation in Research of Informatics (Innovatics) Vol 7, No 1 (2025): March 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i1.11442

Abstract

Stiky tape is a popular snack in Indonesia made from fermented ketan rice. One of the main benefits of eating white cheddar rice is to trigger the digestive system. Excessive consumption can result in a decrease in sweetness and inappropriate texture. Therefore, it is necessary to classify the maturity level of the tape, so that there is no excessive maturity that results in adverse effects on the body and the quality of the tapes.The study aims to test the accuracy of the white tape maturity classification program as well as design and implement a classification system using the Convolutional Neural Network (CNN) method with the VGG16 architecture. The white tape image data set was obtained with the iPhone X camera in jpg format, covering three maturity classes: raw, ripe, and rotten, each consisting of 400 images. The data set is divided into 768 training data, 192 validation data, and 240 test data, then processed through preprocessing stages including resize, augmentation, and rescale. The CNN model was implemented with the VGG16 architecture and tested on various Epochs, producing an accuracy of 0.98 on Epoches 20 and 30, and reaching 0.99 on the 40th. The results of the research showed that the CNN method with VGG-16 architecture was effective in classifying the maturity level of the tape, achieving high accuration and significant consistency as the number of Epochs increased. This implementation is expected to preserve the quality of the tapes and extend the application of modern technology in traditional industries.
Co-Authors Murinto Murinto