Neural Network Back-Propagation Method as Forecasting Technique

Abstract

Uncontrolled population increase has a direct impact on the development of human resource quality, and the rate of economic growth is becoming increasingly challenging. It was the purpose of the study to apply artificial intelligence tools to examine the forecasts of active family planning participants. Between 2019 and 2020, Pematangsiantar's family planning participants will be counted as part of the dataset. The dataset was gathered through observation and interviews. The problem was solved using an artificial intelligence technique with a backpropagation algorithm. The analysis is carried out with the aid of Matlab R2011a. Six other architectural models, including 6-4-1, 6-4-2-1, 6-6-8-1, and 6-8-10-1, were evaluated for their suitability. The 6-4-2-1 architectural model on Backpropagation may be used to forecast the number of active family planning participants with a training accuracy rate of 75% and a test accuracy rate of 88%, according to the study's findings. Results are expected to shed light on the necessity and availability of contraception for Pematangsiantar's active family planning participants.