Hasanah, Hasanah2024-03-052024-03-052023-11PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/11338Unemployment is still widely found in Riau province. There are many factors that influence unemployment, one of which is the level of education completed. Therefore, unemployment prediction is needed to overcome the problem. Prediction is done by using backpropagation neural network method. The purpose of this research is to determine the best model in predicting unemployment based on education in Riau. The best model is determined from the evaluation results of the smallest mean squared error (MSE) and mean absolute percentage error (MAPE) values. From the test results, the best architecture model is obtained, namely model C with an architecture of 8 input layers, 4 hidden neurons, 1 output layer (8-4-1) with 0.01 learning rate. From the evaluation result, model C produces MSE value of 0.0027 and MAPE value of 16.99%. Thus, model C is able to predict unemployment based on education level in Riau well and can be used for further prediction of unemployment based on education.enBackpropagation Neural NetworkMAPEMSEUnemploymentPredictionArticle