Forecasting Analysis Sales of Shrimp Cracker Using Artificial Neural Network Method (ANN)
Analisa Peramalan Penjualan Kerupuk Udang Dengan Menggunakan Metode Artificial Neural Network (ANN)
DOI:
https://doi.org/10.21070/ups.26Keywords:
Prediction, Artificial Neural Network, Roat Mean Square ErrorAbstract
PT. KLM often has problems in terms of raw materials. This company often experiences excess or shortage of raw material stock. Constraints on these raw materials can cause several things, including if the company experiences excess raw materials in the warehouse, it will cause disruption to product transportation and if the raw materials are not treated according to existing standards will cause product damage so that it can make the company lose money. In this study also used an artificial neural network method. The data used is shrimp cracker sales data for 4 years from 2018 to 2021 which is taken from the PPIC section. The results of the research carried out are the results of sales predictions for 12 consecutive periods from January to December as many as 3,370, 1,522, 1,545, 1,681, 1,453, 1,737, 1,844, 1,530, 463, 1,515, 1,477, 1,514 with a roat mean square value. error of 0.120.
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