Implementation of MobileNet V3 In Classifying Butterfly Species with Android and Cloud Based  Application Development

Ihsan Zulfahmi; Said Iskandar Al Idrus; Hermawan Syahputra; Insan Taufik; Kana Saputra S

doi:10.59934/jaiea.v4i2.797

Authors

Ihsan Zulfahmi Universitas Negeri Medan
Said Iskandar Al Idrus Universitas Negeri Medan
Hermawan Syahputra Universitas Negeri Medan
Insan Taufik Universitas Negeri Medan
Kana Saputra S Universitas Negeri Medan

DOI:

https://doi.org/10.59934/jaiea.v4i2.797

Keywords:

MobileNetV3-Large, Butterfly, CNN, GCP, Cloud Run, Android, Deep Learning

Abstract

This research aimed to develop an Android application capable of classifying butterfly species using cloud computing and deep learning technologies. MobileNetV3-Large, a Convolutional Neural Network (CNN) architecture, was employed to process and classify six butterfly species. The dataset was divided into two ratios, 70:30 and 80:20, for training and testing. Evaluation results indicated that the optimal model was achieved with an 80:20 ratio, yielding an accuracy of 94% and precision, recall, and F1-Score values exceeding 90% for each species class. Google Cloud Platform (GCP) was utilized to manage and run the model using the Cloud Run service, enabling the application to function efficiently even with limited resources on Android devices. The application incorporates an encyclopedia of species and a camera scanning feature, making it a valuable educational tool

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References

B. Falakhi, E. F. Achmal, M. Rizaldi, R. R. R. Athallah, and N. Yudistira, "Perbandingan Model AlexNet dan ResNet dalam Klasifikasi Citra Bunga Memanfaatkan Transfer Learning," Jurnal Ilmu Komputer dan Agri-Informatika, vol. 9, no. 1, pp. 70-78, 2022.

E. Barus, K. M. Pardede, and J. A. Putri Br. Manjorang, "Transformasi Digital: Teknologi Cloud Computing dalam Efisiensi Akuntansi," Jurnal Sains dan Teknologi, vol. 5, no. 3, pp. 904-911, 2024.

F. B. Prasetio and T. Wellem, "Perancangan Dan Implementasi Aplikasi Android Untuk Layanan Informasi Pariwisata," IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi, vol. 1, no. 2, pp. 114-132, 2022.

F. F. Maulana and N. Rochmawati, "Klasifikasi Citra Buah Menggunakan Convolutional Neural Network," Journal of Informatics and Computer Science, vol. 1, no. 2, pp. 104-108, 2020.

G. Ashari Rakhmat and M. Fikri Haekal, "Peningkatan Performa MobilenetV3 dengan Squeeze-and-Excitation (Studi Kasus Klasifikasi Kesegaran Ikan Berdasarkan Mata Ikan)," Journal MIND Journal, vol. 8, no. 1, pp. 27-41, 2023.

I. Mahendra and D. T. Eby Yanto, "Sistem Informasi Pengajuan Kredit Berbasis Web Menggunakan Agile Development Methods Pada Bank Bri Unit Kolonel Sugiono," Jurnal Teknologi Dan Open Source, vol. 1, no. 2, pp. 13-24, 2018.

K. Azmi and S. Defit, "Implementasi Convolutional Neural Network (CNN) Untuk Klasifikasi Batik Tanah Liat Sumatera Barat," vol. 16, no. 1, pp. 2580-2582, 2023.

M. M. Lucini, P. J. Van Leeuwen, and M. Pulido, "Model error estimation using the expectation maximization algorithm and a particle flow filter," SIAM-ASA Journal on Uncertainty Quantification, vol. 9, no. 2, pp. 681-707, 2021.

M. Romzi and B. Kurniawan, "Pembelajaran Pemrograman Python Dengan Pendekatan Logika Algoritma," JTIM: Jurnal Teknik Informatika Mahakarya, vol. 3, no. 2, pp. 37-44, 2020.

A. Febriandirza, "Perancangan Aplikasi Absensi Online Dengan Menggunakan Bahasa Pemrograman Kotlin," Pseudocode, vol. 6, no. 1, pp. 53-59, 2019.

A. D. Nugroho and W. M. Baihaqi, "Improved YOLOv5 with Backbone Replacement to MobileNet V3s for School Attribute Detection," SinkrOn, vol. 8, no. 3, pp. 1944-1954, 2023.

A. Mujahid, M. Y. Abdullah, S. Suharya, and A. R. Adriansyah, "Analisis dan Pengembangan Sistem Informasi Pengelolaan Masjid berbasis Mobile dengan Teknologi API Web Service," Jurnal Informatika Terpadu, vol. 7, no. 2, pp. 80-86, 2021.

P. Fernando, I. Junaedi, and A. Budi Yulianto, "Perancangan Sistem Informasi Booking Studio Musik Berbasis Website Di Studio Abe Music Dengan Metode Waterfall," Jurnal Sains dan Teknologi Widyaloka, vol. 2, no. 2, pp. 179-205, 2023.

P. Palupiningsih, A. R. Sujiwanto, and R. R. B. P. Prawirodirjo, "Analisis Perbandingan Performa Model Klasifikasi Kesehatan Daun Tomat menggunakan arsitektur VGG, MobileNet, dan Inception V3," Jurnal Ilmu Komputer dan Agri-Informatika, vol. 10, no. 1, pp. 98-110, 2023.

Y. Miftahuddin and F. Adani, "Sistem Klasifikasi Jenis Kupu-Kupu Menggunakan Visual Geometry Group 16," vol. X, no. X, pp. 1-11, 2022.