Application of Decision Tree Method for Sales Prediction at PT. Cipta Naga Semesta (Mayora Group) North Jakarta for 2023
DOI:
https://doi.org/10.35870/ijsecs.v4i3.2999Keywords:
Decision Tree, Sales Forecasting, Data Analysis Techniques, Predictive Modeling, Operational EfficiencyAbstract
The purpose of this study is to forecast sales of PT. Cipta Naga Semesta, one of the companies owned by Mayora Group headquartered in North Jakarta using the Decision Tree method during 2023. Decision Tree was chosen because this model identifies key attributes that greatly affect sales in the data and has the ability to predict outcomes by recognizing patterns in historical data. The database used in this analysis includes monthly records of sales, promotions, prices, and other economic characteristics. The findings of the study indicate that the Decision Tree method is very effective in providing accurate sales predictions with a low margin of error. The forecast provides valuable perspectives for company management, which can help them design tighter sales strategies and make better inventory decisions, thereby maximizing operational efficiency and profitability. In addition, the exploration of sales prediction models is one of the future works proposed in this study, which recommends practitioners to explore alternative methods to improve forecast accuracy and robustness.
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