Klasifikasi Jenis Burung Cendrawasih Menggunakan Convolutional Neural Network (CNN) Berdasarkan Citra

Thaniket, Rooy Marthen
Rahanra, Musa Henri Janto
Dharsono, Wardhana Wahyu

Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI)
Vol 8 No 1 (2025): Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI)

Birds of paradise are iconic symbols of Indonesia's biodiversity, especially in Papua, with more than 40 recorded species. Manual classification requires specific expertise and is time-consuming. This study aims to develop an automated classification system for birds of paradise using Convolutional Neural Network (CNN), specifically the MobileNetV2 architecture known for its efficiency in image processing. The dataset used comprises three species: Cicinnurus regius, Paradisaea apoda, and Paradisaea rubra. The preprocessing steps include image augmentation, resizing, and normalization. The training results show an accuracy of 98.49% and validation accuracy of 97.50%. Evaluation using a confusion matrix reveals high accuracy and minimal misclassification. This model shows great potential for use in conservation applications and automatic bird species identification