ANALISIS PEMANFAATAN BACKPROPAGATION DAN METODE FUZZY TSUKAMOTO UNTUK MENENTUKAN PREDIKSI PENJUALAN DAN STOK YANG HARUS TERSEDIA

Abstract

Artificial neural networks are now beginning to be developed in various areas of daily life. One of which is in the field of business development. In the field of artificial neural network business is widely used to help solve problems in order to make decisions and predict the occurrence of future circumstances. This research will analyze how the artificial neural network Backpropagation in predicting the sale of a product at once Determine how many stocks the company must provide to accommodate its sales.Bakpropagation is a supervised learning algorithm and is commonly used by perceptrons with multiple layers to change the weights associated with neurons in the hidden layer. The Tsukamoto method is a model of a system capable of providing recommendations and estimates of production quantities based on criteria. Backpropagation method will be applied to estimate sales that will occur in certain month, then Tsukamoto Method will give recommendation of amount that must be in production based on amount of inventory, availability and demand so that company able to know how to be in production