Sales Analysis Using the Forecasting Method

Pataropura, Amesanggeng; Riki, Riki; Saputra, Ariadi

doi:10.32877/bt.v1i3.79

Cited by 6 publications

(4 citation statements)

References 1 publication

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“…Simple moving average (SMA) is a value-smoothing forecasting method that computes the average as the output from a group of input values (Pataropura et al, 2019). The formula for SMA is as follows:…”

Section: Simple Moving Averagementioning

confidence: 99%

Data Analytics Approach for Short-term Sales Forecasts Using Limited Information in E-commerce Marketplace

Chee¹,

Chiew²,

Sarbini³

et al. 2022

AIP

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E-commerce has become very important in our daily lives. Many business transactions are made easier on this platform. Sellers and consumers are the two main parties that gain a lot of benefits from it. Although many sellers are attracted to set up their businesses on this online platform, it also causes challenges such as a highly competitive business environment and unpredictable sales. Thus, we propose a data analytics approach for short-term sales forecasts using limited information in the ecommerce marketplace. Product details are scraped from the e-commerce marketplace using a content scraping tool. Since the information in the e-commerce marketplace is limited and essential, scraped product details are pre-processed and constructed into meaningful data. These data are used in the computation of the forecasting methods. Three types of quantitative forecasting methods are computed and compared. These are simple moving average, dynamic linear regression and exponential smoothing. Three different evaluation metrics, namely mean absolute deviation, mean absolute percentage error and mean squared error, are used for the performance evaluation in order to determine the most suitable forecasting method. In our experiment, we found that the simple moving average has the best forecasting accuracy among other forecasting methods. Therefore, the application of the simple moving average forecasting method is suitable and can be used in the e-commerce marketplace for sales forecasting.

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Section: Simple Moving Averagementioning

confidence: 99%

Data Analytics Approach for Short-term Sales Forecasts Using Limited Information in E-commerce Marketplace

Chee¹,

Chiew²,

Sarbini³

et al. 2022

AIP

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“…Forecasting is the "art and science of predicting future events" [5] [6] [7]. Forecasting itself has types, namely, forecasting can be divided into several types [8].…”

Section: Forecastingmentioning

confidence: 99%

Inventory Management with Forecasting Method: Single Moving Average and Trend Projection

2020

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Inventory management using forecasting methods aims to improve effectiveness and efficiency that facilitate trading businesses in the process of business transactions, improve delivery of information quickly, accurately, and transaction data properly and minimize errors. The system running in the system of selling goods is still manual, that is, it is not well computerized. The method used is forecasting which helps determine the estimated future stock of goods. Single Moving Average and Trend Projection. It can be concluded that the results of implementing this new system can assist trading businesses in recording transactions in the system. We can predict the current flow of goods which has been calculated based on 2 modules that have a connection with the system.

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“…Prediction or forecast is something that will be known or prepared in the future based on past data with structured analysis (Pataropura et al, 2019;Rusmala & Susilawati, 2021;Tahyudin et al, 2021). The benefit of sales forecasting is that it can predict sales accurately from time to time so that a production plan can be made by sales forecasting (Alfons & Batlajery, 2018).…”

Section: Introductionmentioning

confidence: 99%

Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia

Fauzan¹,

Rahayu²,

Handayani³

et al. 2023

J. Inf. Technol. Cyber Secur.

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The market of Fast-Moving Consumer Goods (FMCG) companies in Indonesia is enormous. Unilever has 400 brands in more than 190 countries, making it a global business that is as influential in the consumer product market as it is in Indonesia. Sales forecasting at this company is very useful for planning expenses and the company's total costs on the business strategy. This study uses trend moment method to forecast the sales and earnings of Unilever Indonesia companies at the end of the year. This article aims to test the performance of the trend moment method calculation on the prediction of net sales and profits in FMCG companies. At the end of the analysis process, it can be concluded that forecasting using trend moment method is going very well. This indicator of success is shown by the error level of MAPE, which is below 10%.

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Sales Analysis Using the Forecasting Method

Cited by 6 publications

References 1 publication

Data Analytics Approach for Short-term Sales Forecasts Using Limited Information in E-commerce Marketplace

Data Analytics Approach for Short-term Sales Forecasts Using Limited Information in E-commerce Marketplace

Inventory Management with Forecasting Method: Single Moving Average and Trend Projection

Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia

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