Implementation of the Least Square Method in Website-Based Product Sales Prediction - Alwi, Alfa Rizki; Harahap, Charles Bronson (Marqcha Institute, 2025)
Sales play a crucial role in determining the continuity and growth of a company. PT. Medan Bajaindo, which operates in the steel product sales sector, requires a system capable of accurately predicting future sales to support decision-making and inventory planning. Currently, sales data analysis is still conducted manually, which is inefficient and prone to errors in forecasting. This research aims to design and develop a web-based sales prediction system by applying the Least Square method. The Least Square method is chosen because it can predict data trends based on historical sales patterns with relatively low error rates. The system is developed using web-based programming languages and supported by a database for storing sales data. The testing results show that the developed system can automatically calculate predictions and present sales trend information more quickly, accurately, and structurally compared to the manual method. With this system, the company’s management can more easily plan sales strategies and stock procurement in a timely manner.