Application of Linear Regression Method in Predicting Chicken Egg Sales - Amran Sitohang; Neramayana Br Tarigan; Lira Virna; Allya Dwi Cantika (SEAN Institute, 2025)
This study aims to predict chicken egg sales using a simple linear regression method based on historical sales data for 12 months, from April 2024 to March 2025. This study uses a quantitative approach with a longitudinal study design. The total sampling technique is used because all monthly sales data is analyzed without exception. Data was collected through sales report documentation from a single egg distributor business unit that operated consistently during the study period. Data analysis was carried out through a preprocessing process, calculation of variable values X (month), Y (sales), and calculation of XY and XX to obtain regression coefficients. The results of the calculation show that the linear regression equation obtained is Y=150.1515233− 6.24126X. This shows that there is an average decrease in sales of 6.24 egg boards every month. Furthermore, this regression model is used to predict chicken egg sales in the period April 2025 to March 2026. The predicted results show a continued downward trend, with sales projected to decline drastically to near zero by March 2026. The conclusion of this study is that there is a downward trend in chicken egg sales during the two years of observation. These results provide an early warning for business actors to evaluate business strategies and take anticipatory steps. This research also opens up opportunities for further study of external factors that may affect sales.