Abstract
One of the large real time data storage sectors is in the marketing sector in the form of sales transactions, prices, and availability of goods stored in databases in certain supermarkets.The amount of supermarkets with the digital cash register system allow storing sales transaction data. Therefore this research aims to designed an application that contains two statistical analysis methods, namely Market Basket Analysis and Sales Forecasting using shiny dashboard package in Market Basket Analysis Menu shows various features that can facilitate businessactors in optimizing product layout in a store shelves i.e. summary products, rules table, scatter plot, graph, matrix and grouphed, and Parallel coordinats. While the sales forecasting menu shows various features i.e. a description of the number of stock items, the number of items sold, capital, profit, the highest frequency of goods sold, and the value of parameter predictions for the next periods.
Reference8 articles.
1. Hahsler M et. al. 2018. Mining Association Rules and Frequent Itemsets. R Version 1.6-1. URL:https://cran.r-project.org/web/packages/arules/arules.pdf.
2. Hashler M & Chelluboina S. 2018. Visualizing Association Rules : Introduction to the R-extension Package arulesViz. R version 1.3-1. URL:https://cran.rproject.org/web/packages/arulesViz/vignettes/arulesViz.pdf.
3. Hyndman R, et al. 2018. Forecasting Functions for Time Series and Linear Models. R version:8.4. URL : https://cran.r-project.org/web/packages/forecast/forecast.pdf.
4. Irliana N & Vydia V. 2013. Market Basket Analysis Pada Perusahaan Retail Menggunakan Algoritma Apriori dan Sales Forecasting. Jurnal Informatika 11(1): 13-22.
5. Mazzara S, et. al. 2017. CombiROC: An interactive web tool for selecting accurate marker combinations of omics data. Scientific Reports (Nature Publisher Group), 7, 45477. doi:http://dx.doi.org/10.1038/srep45477.
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