Application of Artificial Neural Network for Forecasting Demand Bottled Drinking Water by Using Back propagation Algorithm

DOI

10.2991/aer.k.220131.036How to use a DOI?

Keywords

Artificial Neural Network; BDW; Back propagation Algorithm; Supervised Learning

Abstract

The erratic demand for bottled drinking water (BDW) products caused the sales target not to be achieved for several periods. One of the efforts that can be made by the management so that the amount of production is correct is by forecasting demand. This study aims to determine the best forecasting model using the Artificial Neural Network (ANN) method with the Backpropagation algorithm, supervised learning. The activation function used is the binary sigmoid function (logsig). Based on the result, the best architectural model is found in neurons 3-4-1 with an MSE value of 0.0002 and a MAPE value of 2.346%.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Prima Denny Sentia
AU  - Andriansyah
AU  - Ilyas Ishak
AU  - Albizzia Haura
PY  - 2022
DA  - 2022/02/01
TI  - Application of Artificial Neural Network for Forecasting Demand Bottled Drinking Water by Using Back propagation Algorithm
BT  - Proceedings of the Conference on Broad Exposure to Science and Technology 2021 (BEST 2021)
PB  - Atlantis Press
SP  - 216
EP  - 222
SN  - 2352-5401
UR  - https://doi.org/10.2991/aer.k.220131.036
DO  - 10.2991/aer.k.220131.036
ID  - Sentia2022
ER  -