Application of fuzzy time series method to determine medical equipment inventory - Iskandar, Rozai; Furqan, Mhd. (Institute of Computer Science (IOCS), 2025)
This study applied the Fuzzy Time Series (FTS) method to forecast monthly stock requirements for medical equipment at PT. Karya Metropolis. The FTS process including interval determination, fuzzification, fuzzy rule formation, and defuzzification successfully identified historical patterns in sales data and produced predictions closely aligned with actual values. Forecast results indicated the next month’s needs for several items, such as 154.5 units of gauze rolls, 129 units of leukocrepe, 26.5 units of hypafix, 25 liters of 95% alcohol, 487.5 oxygen nebulizer masks, 109.5 units of Vaseline swabs, and 61 Maxter gloves. Forecast accuracy was assessed using Mean Absolute Percentage Error (MAPE), where most items showed low error rates, including gauze rolls (6.16%), Vaseline swabs (7.21%), and Maxter gloves (9.28%). However, the oxygen nebulizer mask showed a higher MAPE value of 47.28%, indicating a need for method refinement or integration with other approaches for that item. Overall, the FTS method proved effective in supporting accurate, efficient, and measurable stock planning decisions for medical supplies.