Optimasi Fuzzy Time Series Menggunakan Algoritma Particle Swarm Optimization Untuk Peramalan Jumlah Penduduk Di Kabupaten Probolinggo - Cahyo Adi Prasojo; Budi Darma Setiawan; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Population growth occurs due to the increasing number of births. The impact of population growth is affecting human welfare, Both in the economic, health, social, politic and cultural fields. Therefore it is necessary to forecast the population, to know how fast the rate of population growth. One of the most commonly used forecasting methods is the Fuzzy Time Series (FTS). However, this method still has a deficiency that is on the determination of the value of the interval that is less precise. therefore it is necessary the optimization algorithm to find the optimal value of the interval. This study aims to perform population forecasting in Probolinggo District by using FTS method which will be optimized using Particle Swarm Optimization (PSO) algorithm. Optimization is performed to obtain optimal interval value on FTS and optimal parameter value on PSO. The parameters in the optimized PSO are (Inertial Weight), (velocity constant 1) and (velocity constant 2). The result of the test, that is got the best fitness , and value, is 0,559140, 0,535084 and 0.621134 and parameter value are 0,6, 1.8 and 2.4. Get the best fitness value of the forecasting, is 0.445334.