KLASIFIKASI JENIS BUNGA MENGGUNAKAN METODE MOBILENETV2 DAN RESNET101

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Published: 2025-10-20
Keywords:
Flower, Computer Vision, Convolutional Neural Network, MobileNetV2, ResNet101
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Ferdinand Iskandar

Abstract

The wide variety of flower species makes it difficult for humans to easily distinguish each flower species. With the help of computer vision technology, recognition of flower species can be done by a machine. So that a system can be created that can classify flower species. In this study, a comparison was made between 2 Convolutional Neural Network (CNN) models namely MobileNetV2 and ResNet101 in recognizing 10 types of flowers including phlox, rose, calendula, iris, leucanthemum maximum, bellflower, viola, rudbeckia laciniata, peony, and aquilegia. From the evaluation results, it is found that the best model is MobileNetV2 with the RMSprop optimizer which gets an accuracy of 87%, precision of 91%, recall of 87%, and f1-score of 87%.

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Vol. 20 No. 2 (2025): Jurnal Komputer dan Informatika

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Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

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