JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI JUMLAH PENGANGGURAN DI KOTA BINJAI DENGAN MENGGUNAKAN METODE BACKPROPAGATION
DOI:
https://doi.org/10.59697/jtik.v5i1.580Keywords:
Backpropagation, Unemployment, Prediction.Abstract
Unemployment is a very complex problem because it affects and is influenced by several factors that interact with each other following a pattern that is not always easy to understand. The strategic problem in Binjai City is not much different from that in the Central Government of North Sumatra, namely the high unemployment rate, given the large number of workforce that appears every year, as well as several factors such as age levels and inflation in Binjai City, making it difficult for many people to find work. or what is called unemployment. The lack of maximum efforts by the government and the private sector in creating employment opportunities is one of the triggers for the increasing number of unemployed in Indonesia, especially coupled with the low level of public education and inadequate human resources, which makes people unable to find work. One of the methods used in predicting a data is Artificial Neural Network using the backpropagation method. With a maximum epoch between 0 - 10000 with a learning rate of 0.2 and a target error ranging from 0.01 to 0.1 to get convergent results. The results of the prediction of the number of unemployed can be predicted by some experiencing an average predicted increase and some experiencing a decrease.