Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27084
ชื่อเรื่อง: Data analytics system for product management in retail business
ผู้แต่ง: Rukkamate N.
Rodamporn S.
Kanuengkid A.
Kamonlakorn K.
Keywords: Data analytics
Machine learning
Web application
วันที่เผยแพร่: 2022
สำนักพิมพ์: Institute of Electrical and Electronics Engineers Inc.
บทคัดย่อ: This paper aims to develop a data analytics system for product management in retail businesses based on the Winters' Method and tests the milk sales forecasting model with machine learning using linear regression, random forest, and eXtreme Gradient Boosting (XGBoost). Using Minitab, apply machine learning test data to separate milk statistical analysis with five forecasting methods. Actual sales figures were compared to the difference using the results of the machine learning model and statistical analysis. The results of machine learning show that random forests have more minor deviations than a statistical analysis performed with Minitab that showed Winters' Method (Additive Method) with UHT of less than 7.9 percent. Pasteurized was less than 9.54 percent. Soymilk was less than 12.57 percent. Fermented milk was less than 10.47 percent. The result is a desirable user satisfaction rating of 4.47 out of 5. © 2022 IEEE.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143073344&doi=10.1109%2fICTIIA54654.2022.9935948&partnerID=40&md5=1b88185c4787a3def3f4f40de045dc80
https://ir.swu.ac.th/jspui/handle/123456789/27084
Appears in Collections:Scopus 2022

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