TY - JOUR
AU - Dion Putra
AU - Giri Wahyu Wiriasto
AU - Paniran Paniran
PY - 2024/11/09
Y2 - 2025/04/05
TI - Detection of Lumpy Disease in Livestock Using the MobileNetV2 Architecture Method
JF - Jurnal Bumigora Information Technology (BITe)
JA - BITe
VL - 6
IS - 2
SE - Articles
DO - https://doi.org/10.30812/bite.v6i2.4401
UR - https://journal.universitasbumigora.ac.id/index.php/bite/article/view/4401
AB - Background: Lumpy Skin Disease (LSD) causes skin lesions, decreased milk production, and death in livestock such as cows.Objective: The purpose of this study is to detect LSD disease quickly and accurately using the Convolutional Neural Network (CNN) MobileNetV2 method based on android application.Method: This study uses a quantitative method with a reuse-oriented development approach and the MobileNetV2 algorithm trained with augmentation data and LSD disease image classification.Result: The results of this study are that the MobileNetV2 classification model is able to detect LSD with an accuracy of 95.91%. The developed application makes it easier for farmers to detect diseases early so that they can accelerate preventive measures.Conclusion: The implications of this study indicate that the MobileNetV2 model can improve the effectiveness of disease detection in livestock and can be applied in animal health applications in the field.
ER -