SISTEM PERAMALAN PENJUALAN KOPI BUBUK SELANGIT MENGGUNAKAN METODE WEIGHTED MOVING AVERAGE (WMA) MENGGUNAKAN DATA TIME SERIES BERBASIS FRAMEORK CI (CODEIGNITER)

Glen Jupiter (Universitas Bina Insan)
Armanto Armanto (Universitas Bina Insan)
Nelly Khairani Daulay (Universitas Bina Insan)

Jurnal Komputer dan Teknologi (JUKOMTEK)
Vol 5 No 2 (2026): JUKOMTEK JULI 2026

This study aims to forecast ground coffee sales using the Weighted Moving Average (WMA) method to support decision-making in business planning. The WMA method was selected because it assigns greater weight to recent historical data, thereby enabling a more responsive capture of changes in sales trends. The results indicate that ground coffee sales are projected to experience a stable upward trend in 2025. The model achieved a high level of accuracy, yielding a MAPE of 0.098%, an MAE of 54.463, and an RMSE of 70.683. Although discrepancies occurred in certain periods due to high sales volatility, the WMA method generally tracked actual data patterns effectively and produced realistic estimates. Consequently, the WMA method is a suitable tool for sales forecasting to support production planning, inventory control, and the formulation of more effective sales strategies.