FORECASTING ANALYSIS OF URETHANE BLADE NEEDS ON BELT CLEANER TO MINIMIZE FORECAST ERROR (CASE STUDY AT PT. MS ENGINEERING)
Abstract
- MS Engineering is a company engaged in the field engineering, which is producing belt cleaners for cleaning conveyor belts in mining areas, the cement industry and the power plant. In the belt cleaner, has several parts assembled into one, including metal parts and urethane blade parts. PT MS Engineering has low forecasting accuracy, causing excess stock, especially for parts of urethane blade that have expired. The company only sees based on historical data. Therefore, to overcome these problems, it is necessary to forecast demand with the appropriate method. In this study by comparing several forecasting methods to find the highest error rate. The methods to be used include Single Moving Average, Exponential Smoothing and Weighted Moving Averages. From the discussion and analysis of the three calculation methods above, it is known that the calculation results with the 4 monthly Single Moving Average methods are better and more suitable to be applied by PT. MS Engineering in predicting the needs of Urethane Blade in January 2020, because the method has a lower error rate than the method other. The forecast error rate, MAD (Mean Absolute Deviation) of 58,906 and MSE (Mean Square Error) of 4484.57 with forecast results for January 2020 of 292.5 pcs.
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