PERBANDINGAN METODE SINGLE EXPONENTIAL SMOOTHING DAN SINGLE MOVING AVERAGE DALAM PENENTUAN JUMLAH PENJUALAN PUPUK
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Institusion
Universitas Sriwijaya
Author
M.A.RASYID HILMI (STUDENT ID : 09021181520026)
Yunita Yunita (LECTURER ID : 0006068305)
Kanda Januar Miraswan (LECTURER ID : 0009019002)
Yunita Yunita (LECTURER ID : 0006068305)
Kanda Januar Miraswan (LECTURER ID : 0009019002)
Subject
R858-859.7 Computer applications to medicine. Medical informatics
Datestamp
2019-11-15 05:24:07
Abstract :
The Single Exponential Smoothing Method and the Single Moving Average are forecasting methods that is suitable for predicting short-term data. This study compares between the Single Exponential Smoothing Method and the Single Moving Average Method in predicting fertilizer sales at PT.PUPUK SRIWIDJAJA. To compare these methods, predictions were made for each sale with both methods, then the results of predictions were compared with actual data to take 4 measurements which are Mean Error (ME), Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percent Error (MAPE). Based on the research results, it was found that the best alpha for data organik in Single Exponential Smoothing method was 0,6, and the best alpha for data urea was 0,9. Meanwhile the best moving for data organik in Single Moving Average method was 2, and the best moving for data urea was also 2. Also based on this research, it was found that Single Exponential Smoothing has higher accuracy than Single Moving Average in predicting these data with 0,37 ME difference, 77,93 MAD difference, 285.625,87 MSE difference, and 2,07% MAPE difference for data organik while data urea has -271,86 ME difference, 4.686,12 MAD difference, 348.156.881,79 MSE difference, and 4,05% MAPE difference.
The Single Exponential Smoothing Method and the Single Moving Average are forecasting methods that is suitable for predicting short-term data. This study compares between the Single Exponential Smoothing Method and the Single Moving Average Method in predicting fertilizer sales at PT.PUPUK SRIWIDJAJA. To compare these methods, predictions were made for each sale with both methods, then the results of predictions were compared with actual data to take 4 measurements which are Mean Error (ME), Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Mean Absolute Percent Error (MAPE). Based on the research results, it was found that the best alpha for data organik in Single Exponential Smoothing method was 0,6, and the best alpha for data urea was 0,9. Meanwhile the best moving for data organik in Single Moving Average method was 2, and the best moving for data urea was also 2. Also based on this research, it was found that Single Exponential Smoothing has higher accuracy than Single Moving Average in predicting these data with 0,37 ME difference, 77,93 MAD difference, 285.625,87 MSE difference, and 2,07% MAPE difference for data organik while data urea has -271,86 ME difference, 4.686,12 MAD difference, 348.156.881,79 MSE difference, and 4,05% MAPE difference.
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RAMA_55201_09021181520026.pdf
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