The hybrid-model architectural modelling based on ARIMA-BPNN methods for building materials demands forecasting

Abstract

The development of hybrid acrhitectural model is made to facilitate the decision making in determining the demand for building materials procurement. The ARIMA time series and non-linear BPNN models are selected considered that they are able to have a high degree of accuracy of the generated output. The data used were the secondary data collected in the period of February 2015-October 2016 which consisted of month of sales period, product prices, sales history (per type of building materials), estimated number of renovation projects, estimated number of new construction projects, and number of competitors. This research was conducted through 2 stages, they were; the processing of time series using ARIMA through three basic steps, namely identification, assessment and testing, and diagnostic examination; and the BPNN processing through data training and data testing stages. The produced hybrid architectural model had 99% accuracy with an MSE of 0.00099926 on epoch 975 and training period of 00:00:01. The Regression results showed that the produced model has a high degree of accuracy in generating the ouput of building materials demand forecasting.