Klasifikasi Ketertarikan Anak PAUD Melalui Ekspresi Wajah Menggunakan Metode CNN
Abstract
The character of emotions in children is different from that of adults, where the characteristics of the emotions in childres include, (1) Briefly and ends suddenly, (2) Seems greater or stronger, (3) Temporary or superficial, (4) Frequent, (5) Can be known clearly from behaviour, and (6) Reaction reflects individuality. Emotions that are felt can be expressed through faces, this is continuous with how interested the child is tho the material presented in fornt of him. Measuring the level of interest in PAUD children in this study using CNN. In the process of training the level of interest in PAUD children, the accuracy value of the four models always increases from epoch 25 until 100 with the highest value being the Rajmehra architecture. But during the data testing process, the architecture in this study increased slightly and the highest peak reached an accuracy value of 81.66%. It is 3.33% better than the result obtained with the Rajmehra architecture.
Emosi adalah perasaan atau afeksi yang timbul, ketika seseorang berada dalam suatu keadaan yang dianggap penting oleh individu tersebut. Karakteristik emosi pada anak berbeda dengan karakteristik yang terjadi pada orang dewasa, dimana karekteristik emosi pada anak itu antara lain, (1) Berlangsung singkat dan berakhir tiba-tiba, (2) Terlihat lebih hebat atau kuat, (3) Bersifat sementara atau dangkal, (4) Lebih sering terjadi, (5) Dapat diketahui dengan jelas dari tingkah lakunya, dan (6) Reaksi mencerminkan individualitas. Emosi yang dirasakan dapat diekspresikan melalui wajah, hal ini berkesinambungan dengan seberapa tertariknya anak terhadap tayangan materi yang disajikan dihadapannya. Pengukuran tingkat ketertarikan anak PAUD pada penelitian ini menggunakan CNN. Dalam proses training tingkat ketertarikan anak PAUD, nilai akurasi keempat model selalu mengalami peningkatan mulai dari epoch 25 hingga 100 dengan nilai tertinggi adalah arsitektur Rajmehra. Tetapi saat proses testing data, arsitektur pada penelitian ini mengalami peningkatan secara perlahan dan puncak tertinggi mencapai nilai akurasi 81,66%. Hal tersebut jauh lebih baik 3,33% dibandingkan hasil yang diperoleh dengan arsitektur Rajmehra.
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