Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JEECS (Journal of Electrical Engineering and Computer Sciences)
Oktaviana Isbirotin
Universitas Bhayangkara Surabaya
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Prediction of Skincare Sales Turnover Using the Support Vector Method at the Widya Msglow Sidoarjo Company Oktaviana Isbirotin; Wiwiet Herulambang; Rahmawati Febrifyaning Tias; Rangsang Purnama; Ahmadi
JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 8 No. 2 (2023): JEECS (Journal of Electrical Engineering and Computer Sciences)
Publisher : Fakultas Teknik Universitas Bhayangkara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54732/jeecs.v8i2.10

Abstract

Every entrepreneur will certainly follow technological developments in the business world. MsGlow is one of theskincare businesses. The skincare business is one of the businesses that must compete with rapid and complexchanges, 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 andprecise operational data processing, information system facilities can be an alternative to solving problems in dataprocessing, minimizing errors and accelerating the data processing process. As the number of sales transactionsincreases, there will be a buildup of data that has not been processed optimally. With the above problems, aforecasting 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 SupportVector Machine (SVM) are RBF, Linear, and, Polynomial Degree 2. The results obtained from this research trialshow that the overall forecasting model is good. The accuracy of the three areas obtained with the RBF kernel has arelatively good MAPE. In the accuracy test to predict skincare sales turnover, the three areas got a fairly goodaccuracy value of 94.46%. In the Sidoarjo area, it is predicted that there will be a lot of decrease in turnover in 2023-2024.
Co-Authors Ahmadi Rahmawati Febrifyaning Tias Rangsang Purnama Wiwiet Herulambang