COMPARISON OF MOVING AVERAGE AND EXPONENTIAL SMOOTHING METHODS IN ANALYZING KWH METER STOCK EXPENDITURE DATA

Parida, Merri
Liyanti, Reta

IJISCS (International Journal of Information System and Computer Science)
Vol 8, No 2 (2024): IJISCS (International Journal of Information System and Computer Science)

A common problem that occurs in a company is how to predict future production by utilizing historical data that has been previously recorded, to minimize errors in providing a stock of goods and increasing production efficiency so as not to waste more costs. This research aims to identify and analyze the results of production forecasting using the moving average and exponential smoothing methods in the forecasting calculation process to determine the future stock of goods. Data processing using rapidminer programming, from the prediction results using both methods states that the exponential smoothing method with an alpha value of 0.9 is superior to the moving average method with a request result of 23661.5 MAD = 70.7 and MSE = 12387.9987 smaller than other methods.