Application of Data Mining with Support Vector Machine (SVM) in Selling Prediction Trend of Spiritual Goods (Case Study: PT. X Bali)

Philipus Novenando Mamang Weking (Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University)
I Gusti Ngurah Wira Partha (Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University)
Antonius Ibi Weking (Department of Electrical and Computer Engineering, Udayana University)

International Journal of Engineering and Emerging Technology
Vol 4 No 1 (2019): January - June

Spiritual activities become an inseparable part of human life. To support these spiritual activities, the need for spiritual equipment that supports the process of running a spiritual activity. PT. X Bali is a company that runs the business of selling spiritual goods. The tight competition and economic factors faced make PT. X Bali wants to predict the sale of goods so that they can see whether the sale of spiritual goods is up or down in order to increase the efficiency. The prediction process can be done with data mining technique using the Support Vector Machine (SVM) method. Data that used for prediction is based on stock data and data on goods sold from the total sales results of the last two years. Based on the results of SVM calculations, the level of prediction accuracy results reached 62.5% and the need for spiritual goods in the following year will be predicted to decline