Comparative Analysis Of Fuzzy Time Series And Double Exponential Smoothing Methods In Predicting Medicine Demand At Community Health Centers

Abstract

Drug inventory management in primary health centers requires accurate forecasting to reduce stock-outs, overstock, and logistics inefficiency. This study compares Cheng Fuzzy Time Series (FTS) and Holt Double Exponential Smoothing (DES) for forecasting drug demand at Pajar Bulan Public Health Center. Using LPLPO data, 84 valid drug items were analyzed with January-December 2025 as training data and January-April 2026 as testing data. DES produced a lower MAE, but FTS achieved a better MAPE and was superior on 65.5% of items with valid MAPE. The results indicate that FTS is more robust for fluctuating active drug demand, while DES is suitable for more stable trend patterns.