IMPLEMENTASI METODE SIMPLE MOVING AVERAGE (SMA) MENGGUNAKAN PYTHON UNTUK PERAMALAN STOK OLI AHM - Herri Wijaya; Milad Naufal akbar; Fifi Endah Irawati (Universitas Muhammadiyah Kudus, 2025)
Inefficient inventory management at Toko Mojo Pahit Motor frequently leads to overstocking and stockouts of AHM oil products, a challenge compounded by steadily increasing sales. This study aims to implement the Simple Moving Average forecasting method using Python to predict sales and provide data-driven recommendations for inventory optimization. The research employed a quantitative approach with a case study design, analyzing monthly sales data from 2021 to 2024. The Simple Moving Average method was tested with various time periods and evaluated using Mean Absolute Error to identify the most accurate model. The results indicated that the three-month period model achieved the highest accuracy, yielding a Mean Absolute Error of 18.52. Based on the forecasts from this model, a re-order point of 42 units is recommended, providing a quantitative basis for procurement decisions. The primary limitation of this method is its inability to directly respond to external factors. It is concluded that implementing the Simple Moving Average method with Python offers an effective and practical solution for Toko Mojo Pahit Motor. It is recommended that the store regularly updates its forecasts to maintain accuracy.