PREDICTIONS OF RAINFALL DATA TO KNOW THE CONTENTS OF RESERVOIR USING THE HOLT-WINTERS EXPONENTIAL SMOOTHING MULTIPLICATIVE MODEL METHOD - Nazilatus Sa'idah; Esti Wulandari; Djoko Laksono; Sigit Purwanto (Bajang Institute, 2025)
Rapid technology has given rise to new methods in science. Among these sciences, data prediction is a science that is often used to find out data on events that will appear in the future, one of which is forecasting discharge data. Water data that fills a reservoir can also be predicted by knowing past rainfall data that occurred in that area. This study aims to examine the water content of the Lowayu Reservoir by predicting past rainfall data to find out the rainfall that occurred in 2026. The results of the rainfall data prediction are then transformed into water discharge that will fill the reservoir and then be used to meet water needs for agriculture. The prediction method used is the Holt-Winters exponential smoothing model multiplicative method. The results of the study show that the highest rainfall was obtained in December - January 2024 - 2026 at 220 mm - 224 mm which resulted in a maximum water volume in the reservoir of 213,400,000 liters -217,280,000 liters/month during 2024-2026 with a Mean Average Percentage Error (MAPE) value of 15.8%