Optimasi Fungsi Keanggotaan Fuzzy Menggunakan Algoritma Genetika Dalam Penentuan Kebutuhan Gizi Bayi MPASI - Marwa Mudrikatussalamah; Candra Dewi; Bayu Rahayudi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
In determining the nutritional needs for infants required several factors, one of the strengthening factors is to determine the nutritional status of infants. In determining the nutritional status of infants, it need a rangewhhich contain of the limit on each nutitional category. The method used in this determination is fuzzy tsukamoto which will be used for the optimization of membership function with genetic algorithm. Genetic algorithms are used to form the boundaries formed on a chromosome. Boundaries of grade that have been used in genetic algorithm will be a function grade of membership in fuzzy tsukamoto. The next process is fuzzy tsukamoto will process the data in accordance with the value that has been optimized by the genetic algorithm to determine the final result. Further testing is done to determine the best parameters in making chromosomes. The Test are obtained an average accuracy of 53.5%. Accuracy is obtained from the calculation of the optimization results compared with the value of the expert.