Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal IPTEK
Luge, Miclyael
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Computer Science & IT Industrial & Manufacturing Engineering Mechanical Engineering

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

Found 1 Documents
Search

 1 
Implementation of Convolutional Neural Network in Detecting Avocado Ripeness Level Luge, Miclyael; Indra, Zulfahmi; Syahputra, Hermawan; Al Idrus, Said Iskandar; S, Kana Saputra
Jurnal IPTEK Vol 29, No 1 (2025)
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2025.v29i1.6737

Abstract

Squeezing avocados to determine ripeness can cause physical damage or bruising, reducing the fruit’s quality and resulting in losses for sellers and buyers. This research aims to develop an Android-based mobile application to detect avocado ripeness based on skin color, avoiding physical damage to the fruit. The study uses three simple Convolutional Neural Network architectures to evaluate the algorithm’s ability to detect avocado ripeness. The dataset includes 385 images across four classes: immature, half-ripe, ripe, and overripe (74 images each), and an additional 89 images for the non-avocado class. The model was trained with learning rates of 0.001, 0.0001, and 0.00001. The architecture with the most convolutional layers achieved the best performance with a 0.001 learning rate, yielding a test accuracy of 94.15%, a test loss of 19.28%, and an F1-score of 94.0%. The best model was then converted to TFLite format and successfully integrated into an Android application that functions effectively.
Co-Authors Hermawan Syahputra Kana Saputra S Said . Iskandar Zulfahmi Indra, Zulfahmi