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VOLUME 1 Edisi 2 , Nopember 2016
Smoothing Data Fluktuatif dengan Exponential Smoothing Studi Kasus Data Curah Hujan |
Universitas Mercu Buana Yogyakarta |
The fluctuated data is data that contains noise. Smoothing is one way to eliminate noise in the data fluctuate. Data smoothing is aimed at refining the data to improve the accuracy of predictions. In this research will compare some smoothing methods that appropriate for it; with case studies is rainfall data. The methods have been compared are exponential smoothing, moving average 1 and moving average 2.The results showed exponential smoothing produce result data processing the most delicate, smooth curve. So that for the case of rainfall data exponential smoothing is better than moving average 1 and 2.The rainfall data used is the rainfall data Banggai province in 2004-2009. Smoothing data is volatile in the case of rainfall data using one of the methods Moving Average, Moving Average 2, and Exponential Smoothing obtained best results when using Moving Average 2. With the smallest MAE value of 32.67. |
fluctuate data,rainfall, smoothing, and exponential smoothing |
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