ANN Back Propagation in forecasting and policy analysis on family planning programs: A case study in NTB Province. Issue 1 (May 2021) - Syaharuddin; Supriyanto, E E; Septyanun, N; Harun, R R; Islahudin; Apriansyah, D; Saputra, E
Abstract: Various government programs and policies are aimed at improving the welfare of the community. One of them is implementing a family planning program to suppress high population growth. The research aims to implement the artificial neural network architecture of the Back Propagation method of two hidden layers to see an increase in active users of the family planning program on three types of programs namely implants, injections, and pills. The data used include family planning data of ten districts in NTB province consisting of 165 input data. Predicted results showed that the best architecture with an accuracy rate of 99.21%, obtained by the value of learning rate of 0.8, the activation function of each layer is logsig, and the training method is TRAINRP. Besides, obtained information that the average decline in the user type of pills in each district/city. While in other types there is an increase of 8% on Lombok Island, while on Sumbawa Island amounted to 50%.