Penerapan Metode Yolov5 dan Teknologi Text-To-Speech dalam Aplikasi Pengenalan Abjad dan Objek Sekitar untuk Anak Usia Dini

  • Atika Rahmi Putri Politeknik Negeri Padang
  • Ratna Dewi Politeknik Negeri Padang
  • Ramiati Ramiati Politeknik Negeri Padang
Keywords: Early Childhood, YOLO, Text-to-Speech

Abstract

Technological developments have provided significant benefits for various levels of society, including young children. There are several internal and external factors that can hinder children from remembering the alphabet and objects around them. To overcome these challenges, an innovative and interesting approach is needed to increase children's interest and involvement in learning to recognize alphabets and objects. Research has been carried out to develop an interactive learning media aimed at early childhood using an artificial intelligence approach. The You Only Look Once (YOLO) algorithm will be used to detect letters and surrounding objects in real-time, while Text-to-Speech (TTS) technology is used to convert text into sound. The dataset consists of 2511 images with 36 classes, including alphabets, fruits, animals, and stationery. In this research, the YOLOv5s method obtained a significant level of accuracy, reaching 85% so it could work well in detecting objects.

 

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References

[1] Intan Ika Puspita Sari, “Persepsi Guru Terhadap Sosial Emosi Anak Usia Dini Dan Faktor Yang Memengaruhi”, 2020.
[2] D. I. Mulyana, M. F. Lazuardi, and M. B. Yel, “Deteksi Bahasa Isyarat Dalam Pengenalan Huruf Hijaiyah Dengan Metode YOLOV5,” Jurnal Teknik Elektro dan Komputasi (ELKOM), vol. 4, no. 2, pp. 145–151, Aug. 2022, doi: 10.32528/elkom.v4i2.8145.
[3] I. Yuni Wulandari, N. Indroasyoko, R. Mudia Alti, Y. N. Asri, and R. Hidayat, “Pengenalan Sistem Deteksi Objek untuk Anak Usia Dini Menggunakan Pemrograman Python,” remik, vol. 6, no. 4, pp. 664–673, Oct. 2022, doi: 10.33395/remik.v6i4.11772.
[4] S. Kahfi, “Perancangan Aplikasi Text To Speech Dalam Pengucapan Kata Bahasa Jepang Berbasis Android.”
[5] O. E. Karlina and D. Indarti, “Pengenalan Objek Makanan Cepat Saji Pada Video Dan Real Time Webcam Menggunakan Metode You Look Only Once (YOLO),” Jurnal Ilmiah Informatika Komputer, vol. 24, no. 3, pp. 199–208, 2019, doi: 10.35760/ik.2019.v24i3.2362.
[6] A. Wibowo, L. Lusiana, and T. K. Dewi, “Implementasi Algoritma Deep Learning You Only Look Once (YOLOv5) Untuk Deteksi Buah Segar Dan Busuk,” Paspalum: Jurnal Ilmiah Pertanian, vol. 11, no. 1, p. 123, Mar. 2023, doi: 10.35138/paspalum.v11i1.489.
[7] D. I. Mulyana and M. A. Rofik, “Implementasi Deteksi Real Time Klasifikasi Jenis Kendaraan Di Indonesia Menggunakan Metode YOLOV5.”
[8] L. Rahma, H. Syaputra, A. H. Mirza, and S. D. Purnamasari, “Objek Deteksi Makanan Khas Palembang Menggunakan Algoritma YOLO (You Only Look Once),” 2021.
[9] Khairunnas, Eko Mulyanto Yuniarno daAhmad Zaini, “Pembuatan Modul Deteksi Objek Manusia Menggunakan Metode YOLO untuk Mobile Robot ”, 2021.
[10] Hasbi Dawami , Ema Rachmawati , Mahmud Dwi Sulistiyo “Deteksi Penggunaan Masker Wajah Menggunakan Yolov5”, 2023.
[11] F. Rofii, G. Priyandoko, M. I. Fanani, and A. Suraji, “Vehicle Counting Accuracy Improvement By Identity Sequences Detection Based on Yolov4 Deep Neural Networks,” TEKNIK, vol. 42, no. 2, pp. 169–177, Aug. 2021, doi: 10.14710/teknik.v42i2.37019.
Published
2024-02-22
How to Cite
Putri, A., Dewi, R., & Ramiati, R. (2024, February 22). Penerapan Metode Yolov5 dan Teknologi Text-To-Speech dalam Aplikasi Pengenalan Abjad dan Objek Sekitar untuk Anak Usia Dini. Elektron : Jurnal Ilmiah, 94-101. https://doi.org/https://doi.org/10.30630/eji.0.0.423
Section
Articles