Raw Material Cost Prediction Planning and Ready-Mix Product Sales Using Adaptive Linear Neural Network Method

Abstract

An important thing that needs to be considered to ensure the successful implementation of the project is planning. The current problem with RMC is the non-achievement of the target, which causes the company's condition to be not optimal. Stable production cost projections on construction projects have been a problem and a serious concern, especially for project contractors. Often, there is a deviation between the projected initial costs and the actual ones at the construction site. Production predictions need to be made to determine the accuracy of these needs. This study aims to predict the needs of production and raw materials in an industry and can accommodate the calculation of estimated profits. Prediction of an industry's production and raw material needs can be used as a reference in calculating profit estimates. The ADALINE method is a neural system consisting of several nodes. A node requires several input processes to produce one output, which can be used as a predictive model. The results show that the actual and simulation data results using the ADALINE model have 100% conformity. This shows that the ADALINE model on the neural network can also function as one of the prediction model choices in addition to performing a prediction function. Prediction results using neural networks are one of the alternative solutions for utilizing prediction models other than other prediction models.