Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal of Computer Science and Informatics Engineering (J-Cosine)
Wicaksono, Eko Prasetyo
Unknown Affiliation
Computer Science & IT

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

Found 1 Documents
Search

 1 
Studi Pengembangan Sistem Pengenalan Individu Sapi Berbasis Biometrik Muzzle Menggunakan Model Mobilenetv2: Study on the Development of Cattle Individual Recognition System from Muzzle Images Based on MobileNetV2 Model Giri Wahyu Wiriasto; Misbahuddin; Rachman, A. Sjamjiar; Iqbal, Muhamad Syamsu; Budiman, Djul Fikry; Akbar, Lalu Ahmad Syamsul Irfan; Hartawan, Bagi; Wicaksono, Eko Prasetyo
Journal of Computer Science and Informatics Engineering (J-Cosine) Vol 8 No 1 (2024): Juni 2024
Publisher : Informatics Engineering Dept., Faculty of Engineering, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jcosine.v8i1.594

Abstract

In general, in cattle farming, individual identification is often done using text numbers on the cattle's ears, which is considered efficient. However, field observations reveal limitations of this technique, particularly in terms of data redundancy and new registration validation. Sometimes, errors can occur when cattle identity numbers are exchanged between the farm and the livestock market. Therefore, an intelligent biometric identification system attached to each cattle, such as the pattern on the muzzle, similar to human fingerprints, is needed. In this study, we collected and published primary cattle muzzle data as a dataset in a cloud repository. We also implemented the use of muzzle image data with a convolutional neural network algorithm in TensorFlow as a step for further development. The recognition implementation using the MobileNetV2 architecture resulted in an 83% accuracy rate for 30 individual cattle classes out of a total of 210 primary dataset divided into training and testing data.
Co-Authors A. Sjamsjiar Rachman Djul Fikry Budiman, Djul Fikry Giri Wahyu Wiriasto Hartawan, Bagi Irfan Akbar, L. Ahmad Syamsul Misbahuddin Muhamad Syamsu Iqbal