Proceedings of the 4th International Conference on Social Science, Humanity and Public Health, ICoSHIP 2023, 18-19 November 2023, Surabaya, East Java, Indonesia

Research Article

Interactive Learning Media for Fruit Recognition in Early Childhood Using Backpropagation

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  • @INPROCEEDINGS{10.4108/eai.18-11-2023.2342565,
        author={Zilvanhisna Emka Fitri and Siti Ingefatul Komariah and Lalitya Nindita Sahenda and Victor  Phoa and Reski Yulina Widiastuti and Arizal Mujibtamala Nanda Imron},
        title={ Interactive Learning Media for Fruit Recognition in Early Childhood Using Backpropagation},
        proceedings={Proceedings of the 4th International Conference on Social Science, Humanity and Public Health, ICoSHIP 2023, 18-19 November 2023, Surabaya, East Java, Indonesia},
        publisher={EAI},
        proceedings_a={ICOSHIP},
        year={2024},
        month={1},
        keywords={backpropagation computer vision fruit recognition interactive learning media},
        doi={10.4108/eai.18-11-2023.2342565}
    }
    
  • Zilvanhisna Emka Fitri
    Siti Ingefatul Komariah
    Lalitya Nindita Sahenda
    Victor Phoa
    Reski Yulina Widiastuti
    Arizal Mujibtamala Nanda Imron
    Year: 2024
    Interactive Learning Media for Fruit Recognition in Early Childhood Using Backpropagation
    ICOSHIP
    EAI
    DOI: 10.4108/eai.18-11-2023.2342565
Zilvanhisna Emka Fitri1,*, Siti Ingefatul Komariah1, Lalitya Nindita Sahenda1, Victor Phoa1, Reski Yulina Widiastuti2, Arizal Mujibtamala Nanda Imron3
  • 1: Department of Information Technology, Politeknik Negeri Jember
  • 2: Department of Early Childhood Teacher Education, Universitas Jember
  • 3: Department of Electrical Engineering, Universitas Jember
*Contact email: zilvanhisnaef@polije.ac.id

Abstract

The challenges faced by early childhood education in rural areas include an inadequate number of teachers, inadequate facilities and infrastructure, and limited foreign language skills of students. To solve these problems, an interactive, easy, and interesting learning media was created to make students participate actively, help them recognise objects in foreign languages, and adjust the school need (especially schools with a limited number of teachers). Fruit was chosen as the subject of the study because students recognise various popular fruits but do not know their names in English. Computer vision with the backpropagation method was applied to classify and identify 11 types or 789 images of popular fruits. There are seven parameters learned such as red, green, blue, area, perimeter, shape, and diameter colour features. The optimal learning rate of 0.4 and maximum iterations of 500 resulted in a system accuracy rate of 100%.