Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer)
Muhammad Trihardyansyah
STIKOM Tunas Bangsa
Computer Science & IT

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

Found 1 Documents
Search

 1 
WASTE CLASSIFICATION USING TRANSFER LEARNING WITH MOBILENETV2 TO SUPPORT ENVIRONMENTAL MANAGEMENT Muhammad Trihardyansyah; M Safii; Sundari Retno Andani
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 12 No. 1 (2026): JITK Issue August 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v12i1.7757

Abstract

Efficient waste management requires an accurate automatic classification system for organic and recyclable categories. This study aims to develop a deep learning-based waste classification model using the MobileNetV2 architecture with a transfer learning approach. The main contribution of this study lies in the modification of the architecture through fine-tuning techniques and the integration of a 0.5 dropout layer specifically designed to address the problems of overfitting and class imbalance in waste image data. Test results show that the optimized MobileNetV2 model significantly improves classification performance, achieving an accuracy of 93%. This proposed model is proven to be more adaptive and substantially superior compared to standard architectures and comparable architectures such as ResNet.
Co-Authors M Safii Sundari Retno Andani