Pelatihan Feedforward Neural Network Menggunakan PSO untuk Prediksi Jumlah Pengangguran Terbuka di Indonesia - Bayu Septyo Adi; Dian Eka Ratnawati; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2017)
Open unemployment is a problem who faced by Indonesia in every year. In Indonesia, the number of an open unemployment is still in the high level. There are many factors influence the number of open unemployment, the one of that factor is the number of employement not comparable with the number of labor force. When the number of unemployment at the high level, it can influence the other sector, especially at the economy sector. Because of the number of unemployment is high, national income getting decrease and poorness getting increase. Prediction the number of open unemployment, can be expect to help government and other agence to decreasing the number of open unemployment in Indonesian. Feedforward Neural Network is model from artificial neural network which can be implemented for prediction. Backpropagation algorithm can be replaced by Particle Swarm Optimization Algorithm (PSO) for training Feedforward Neural Network . The result in this research, average value of error which is calculated by Average Forecast Error Rate (AFER) is 2.71399%. Based on value of AFER in this reaserch, Feedforward Neural Network trained by PSO method can be using for predicting the number of open unemployment in Indonesia with better accuracy.