Predicting Population Growth Using Artificial Neural Network by Method Backpropagation (Case Study: Durian Lingga Village) - Surbakti, Della Oksa Brina Br Surbakti (Journal of Artificial Intelligence and Engineering Applications (JAIEA), 2025)
This study aims to predict population growth in Durian Lingga Village using the Artificial Neural Network (JST) Backpropagation method. The background of this research is based on a significant increase in population from 2005 to 2024, which poses various challenges in village development planning. The data used in this study is data on the population of Durian Lingga Village from the Central Statistics Agency (BPS) of Langkat Regency during the period 2005–2024. The research method used is quantitative with an experimental approach, where the data is divided into training data and test data, then processed using a 2-5-1 network architecture with a learning rate of 0.05, a target error of 0.02, and a maximum of 1000 epochs.