Implementasi Algoritma Genetika Pada Metode AHP dan SAW untuk Rekomendasi Varietas Unggul Tanaman Tebu (Studi Kasus: Pusat Penelitian Gula PTPN X Jengkol) - Nilna Fadhila Ganies; Dian Eka Ratnawati; Bayu Rahayudi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2017)
Sugarcane varieties are one of the main factors that determine the yield of quality cane productivity. In this study used several criteria to determine the recommendation of superior varieties of sugar cane that is the number of stems, stem diameter, stem height, brix, nirs1, nirs2, nirs3, and nirs4. In order to get the recommendation of superior varieties of cane that is optimal, then in this research used genetic algorithm. The genetic algorithm will optimize the weight value on the AHP and SAW methods. In the process of genetic algorithm the representation of the chromosome used is real code, with a gene length of 28, which is adjusted by the number of varieties criteria. In the reproduction process, the crossover method used is the extended intermediate crossover, and the mutation method used is random mutation. For fitness value obtained from the calculation of accuracy on SAW. While the selection method used is elitism selection, by choosing the highest fitness value as much as the population size. From the test results obtained optimal parameters that the population size of 50 and many generations of 50, with the average fitness of 0.912 so that the obtained accuracy of 91.2%