IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK PADA PENGENALAN EKSPRESI WAJAH UNTUK ANAK USIA DINI

Octaviani, Yohana and Wahyuningsih, Yulia (2023) IMPLEMENTASI CONVOLUTIONAL NEURAL NETWORK PADA PENGENALAN EKSPRESI WAJAH UNTUK ANAK USIA DINI. In: Prosiding Seminar Nasional Ilmu Terapan 2023. (SNITER), VII (1). Universitas Widya Kartika Surabaya, Surabaya, T14-1-T14-8. ISBN 2597-7067

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Abstract

Early age is a golden age that can quickly develop memory to capture everything in the surrounding environment, both behavior and words. Education in early childhood is important for social-emotional training in children. Early childhood facial expressions also indirectly reveal the contents of the child's mind which can be sustainable in daily behavior which affects learning for early childhood growth and development. To avoid inhibiting early childhood growth, the face expression recognition model can be used to help identify children's emotional conditions by recognizing facial expressions. This face expression recognition model is built by applying CNN (Convolutional Neural Network) intelligence and using OpenCV using the Django framework. The dataset used in this research is a collection of faces of every early childhood from various ethnicities. From the research and model-building process that has been carried out, the output display of facial expression detection results is obtained in the form of a percentage and description of the child's expression. The purpose of detecting children's faces is to recognize the emotional condition of a child as a reference for taking the right steps to behave and act in educating early childhood.

Item Type:	Book Section
Uncontrolled Keywords:	Anak Usia Dini, Ekspresi, Pengenalan Ekspresi Wajah, Convolutional Neural Network
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	Fakultas Teknik > Prodi Ilmu Informatika
Depositing User:	Yulia Wahyuningsih
Date Deposited:	13 Mar 2025 03:09
Last Modified:	14 Mar 2025 03:52
URI:	http://repositori.ukdc.ac.id/id/eprint/1802

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