ANALISIS PREDIKSI PROFIT PADA TOKO ESKA DENGAN METODE REGRESI LINEAR - Sanjaya, Rizki Dwi (JATISI, 2025)
Eska Store, as a grocery store business, faces challenges in predicting profits accurately for more efficient business planning. This study aims to develop a profit prediction model using a simple linear regression method, which analyzes the relationship between the number of orders and Eska store revenue for three years, namely 2022 to 2024. Based on the results of the analysis, it was found that linear regression is effective in modeling the relationship between the independent variable (number of orders) and the dependent variable (revenue), with an R² value reaching 0.88 to 0.95. From the prediction results, this model shows that each additional order can increase revenue by around IDR 54,482.87 in 2022, IDR 25,163.94 in 2023, and IDR 47,782.64 in 2024. In addition, the results of the model evaluation show that although there are some errors in the prediction, overall this model can provide fairly accurate results for projecting revenue based on the number of orders. This study suggests that Eska Store uses this model periodically to support better decision making in terms of marketing strategy and production planning. It is expected that by using this linear regression-based prediction model, Eska Store can improve operational efficiency and profitability sustainably. Keywords: Number of Orders, Prediction Model, Profit Prediction, Revenue, Simple Linear Regression