Optimasi Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika pada Penentuan Prioritas Penerima Zakat - Alfiani Fitri; Wayan Firdaus Mahmudy (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Before distributing zakat, required the selection data of recepients by considering some of its criteria because the scholarship must be received by people who are truly in need. The amount of data along with the various criteria that lead to the selection time to produce a long lasting decision. The system of priority SOS scholarship recipients are expected to produce a recommendation candidate who is suitable to receive the zakat with a relatively short time. In some studies mention that the use of fuzzy Tsukamoto methods sometimes does not necessarily produce the optimal final result. In this study, the accuracy of the test results by using fuzzy Tsukamoto alone is 0.725. One of the technique that can be used to provide a more optimal final result is the optimization of limited membership functions using genetic algorithms. The chromosome representation which is used is real-coded, crossover technique using a one-cut-point crossover, mutation techniques using random mutation and chromosomal repair using a hill climbing algorithm. The calculation result of the accuracy system by using the Spearman correlation in the optimization of Tsukamoto fuzzy membership using genetic algorithms with chromosomal repair mechanism is 0.986. While the accuracy test results of the optimization system of Tsukamoto fuzzy membership by using a genetic algorithm without chromosomal repair mechanism is 0.845. The accuracy results shows the increase of the accuracy value with the function optimization of Tsukamoto fuzzy membership by using the genetic algorithms and chromosome repairs with hill climbing.