Sales Forecasting Using the SARIMA (Seasonal Autoregressive Integrated Moving Average) Method on Staple Rice Seeds of the Inpari 32 HDB Variety at PT ABC Banyuwangi
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Rizka Putri Ramadhani*
PT ABC Banyuwangi faces challenges in meeting the demand for rice seeds, especially for the Inpari 32 HDB variety, due to mismatches between inventory and market demand. This issue affects the availability of seeds that match market needs. To address this problem, this study applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) method to forecast the sales of Inpari 32 HDB rice seeds for the year 2025. Historical sales data is analyzed using the SARIMA model to identify seasonal patterns and generate more accurate demand projections. This approach is expected to provide a clearer picture of future rice seed demand. The analysis results show that the SARIMA model provides fairly accurate forecasts, with a Mean Absolute Percentage Error (MAPE) of 6.1%, demonstrating the model's effectiveness in predicting the demand for Inpari 32 HDB rice seeds. With these findings, the company can make more informed decisions in inventory planning and supply chain management. More accurate projections will help PT ABC ensure seed availability aligns with market demand, thus improving distribution efficiency and reducing the risk of seed shortages in the market.
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