Optimasi Fungsi Keanggotaan Fuzzy Dua Tahap menggunakan Algoritme Genetika untuk Penentuan Bakat dan Tingkat Persentase Kecerdasan Anak - Khairiyyah Nur Aisyah; Imam Cholissodin; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Every child has unequal talents and abilities. But not all parents can recognize about the talent that is actually owned by their child. Many parents are misjudge about the potential related to their child. As a result, many children do a subject which not appropriate with the passion they had and can not develop in their profession because of the minimum passion to it. With a system that can determine the talent and intelligence, it is expected that there is a good synergy between teachers and parents to provide an appropriate guidance accordance to the ability owned by them. The processes did on this research consists of 2-stages fuzzy.. The first stage is the determination of talent with Fuzzy Logic and the second stage is determining the percentage of child's intelligence level with Fuzzy Inference System Tsukamoto. The membership function of both will be optimized using Genetic Algorithm to get more optimal result. The accuracy obtained after the optimization with Genetic Algorithm is 87.91%, 27.08% better than without using optimization with an accuracy of 60.83%. The best fitness value was variation of chromosome with 7 genes, population size 100, number of generation is 70, and combination cr=0,8 and mr=0,2.