Implementation of Least Square Algorithm to Predict Monthly Revenue (Case Study: Djuju’s Grocery Store)
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Abstract
Business owners need to estimate their revenue, which is crucial for the sustainability of their operations. Thus, entrepreneurs such as micro, small, and medium-sized business owners, as well as owners of grocery stores, leverage technological advancements to maximize their sales operations. However, manual sales activities can pose challenges for managing sales data, such as disorganized sales record keeping, failure to record sales of high-volume customers, and time-consuming manual reporting for revenue predictions. To address these issues, researchers have developed a revenue prediction information system. In this study, revenue and profit predictions for the following period were calculated using the Least Square algorithm with the Mean Absolute Percentage Error (MAPE). An example calculation for a 12-month period resulted in a revenue forecast of Rp. 2,837,687.76 for the month of June 2023 with a MAPE of 12.71%.
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