Prediction of Skincare Sales Turnover Using the Support Vector Method at the Widya Msglow Sidoarjo Company
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Abstract
Every entrepreneur will certainly follow technological developments in the business world. MsGlow is one of the
skincare businesses. The skincare business is one of the businesses that must compete with rapid and complex
changes, and this very competitive makes business people have to think of strategies for business continuity in order to compete and also survive. One way that can be done is to utilize existing sales data. The importance of fast and
precise operational data processing, information system facilities can be an alternative to solving problems in data
processing, minimizing errors and accelerating the data processing process. As the number of sales transactions
increases, there will be a buildup of data that has not been processed optimally. With the above problems, a
forecasting system was created that can forecast skincare sales turnover using the Support Vector Machine (SVM)
method. In this study, turnover in several areas will be forecasted. The kernel function variations used in Support
Vector Machine (SVM) are RBF, Linear, and, Polynomial Degree 2. The results obtained from this research trial
show that the overall forecasting model is good. The accuracy of the three areas obtained with the RBF kernel has a
relatively good MAPE. In the accuracy test to predict skincare sales turnover, the three areas got a fairly good
accuracy value of 94.46%. In the Sidoarjo area, it is predicted that there will be a lot of decrease in turnover in 2023-
2024.
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