Forecasting Analysis of Consumer Goods Demand using Neural Networks and ARIMA

Forecasting Analysis of Consumer Goods Demand using Neural Networks and ARIMA

Accurate forecasting of consumer demand for goods is extremely important as it allows companies to provide the right amount of goods at the right time. Autoregressive integrated moving average (ARIMA) is a popular method for forecasting time series data, and previous studies have shown that ARIM...

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Bibliographic Details
Main Authors: Arian Dhini, Isti Surjandari, Muhammad Riefqi, Maya Arlini Puspasari
Format: Article
Language:English
Published: Universitas Indonesia 2015-12-01
Series:International Journal of Technology
Subjects:
ARIMA, Consumer goods, Forecasting, Neural network
Online Access:http://ijtech.eng.ui.ac.id/article/view/1430

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