Identification of Children's Personalities as Recommendations for Guidance for Teachers and Parents Using Machine Learning
Abstract
— Kepribadian seseorang mencerminkan identitas individu mereka, yang tidak selalu terlihat secara fisik. Kepribadian dapat dipengaruhi oleh lingkungan, keluarga, dan sifat bawaan sejak lahir. Kepribadian anak yang terbentuk melalui gaya pengasuhan di rumah secara signifikan berdampak pada lingkungan sekolahnya, sehingga penting bagi orang tua dan guru untuk memahami kepribadian anak agar dapat memberikan dukungan yang tepat. Namun, tes psikologi yang ada saat ini yang digunakan untuk menilai kepribadian anak tidak efektif karena durasinya yang panjang. Sehingga diperlukan sistem berbasis machine learning yang mampu mengidentifikasi kepribadian anak melalui analisis garis telapak tangan. Hasil pengujian menunjukkan bahwa sistem dapat mengidentifikasi kepribadian anak dengan akurasi yang tinggi. Algoritma pendeteksi garis telapak tangan mencapai akurasi 100%, dengan mAP50 sebesar 99,5% dan mAP50-95 sebesar 97,4%.Algoritma klasifikasi menunjukkan akurasi 92,3% pada data latih dan 92,2% pada data uji untuk model pertama, dan akurasi 100% pada data latih dan 93,3% pada data uji untuk model kedua. Pengujian sistem deteksi pada aplikasi menunjukkan akurasi 100%.
Kata kunci— kepribadian anak, pembelajaran mesin, analisis garis telapak tangan
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