Sales Forcasting System With Weighted Moving Average On Gajah Bintang Company

Yudianto, Ardyta (2019) Sales Forcasting System With Weighted Moving Average On Gajah Bintang Company. Other thesis, UNIKA SOEGIJAPRANATA SEMARANG.

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Gajah Bintang company is a distributor and shop selling various kinds of rice and sticky rice that have many customers from various groups of people, from housewives, small traders, restaurants, to large class buyers. As one of the business ventures, Gajah Bintang Company often experiences problems in predicting the number of products that must be bought to suppliers every month so sometimes the stock in the Gajah Bintang Company is excessive and sometimes less in number, because there is no system that helps predict the number of products to buy. Therefore, we offer solutions to these problems with an application system that can calculate future sales predictions at Gajah Bintang Company. The data used in this system is obtained from the bookkeeping of product sales that are carried out every day by management, which is then converted into E-data in the form of a text database. The next stage is the process of data classification using the Weighted Forcasting Moving Average method which will give results in the form of predictive values that will be compared with existing data testing. This project will produce a prediction system using data from the sales of Gajah Bintang Company for several periods which are then managed by the Forcasting Weighted Moving Average method and generate predictive values from sales in the future, accompanied by accuracy values in the form of predictive error using the Mean Absolute Deviation method. Keyword: Forecasting, Weigthed Moving Average, Prediction, Forcasting product, Single Moving Average

Item Type: Thesis (Other)
Subjects: 600 Technology (Applied sciences) > 650 Management > 658 Management > Sales management
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 22 Nov 2019 01:14
Last Modified: 20 Nov 2020 03:08

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