Electronic Resource

Analisis komparasi metode neural network dan autoregressive integrated moving average (ARIMA) sebagai metode peramalan penjualan : studi kasus di Better Hearing indonesia

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The purpose of this research is to find the best method of predicting the
level of sales based on previous data conditions. There are several methods that
are often used for forecasting in business, such as moving averages, exponential
smoothing, and ARIMA. In this study using two methods which will then be
compared, Neural Network and ARIMA. Neural Network is a new method of
recent years applied for business forecasting. The data used are from 2010 to 2014
sales data. The results of this study stated that the model of Neural Network to
forecast sales better than ARIMA. This is based on the level of error that is owned
by Neural Network lower than ARIMA. Neural Network also has an average
accuracy rate higher than ARIMA.

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Availability

Detail Information

Series Title

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Call Number

Ref 2x4.27 Nur a

Publisher

Bogor : STEI TAZKIA., 2016

Collation

BMI

Language

Indonesia

ISBN/ISSN

NIM. S. 1216.191

Classification

2x4.27

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

ARIMA
Sales forecasting
Neural Network

Specific Detail Info

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Statement of Responsibility

Masikah Solihati Nur

Other version/related

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