Method EWMA (Exponentially Weighted Moving Average) as a Filter to Fine and Remove Noise on Time Series Data

Abstract The Moving Average method is the most common filter in Digital Signal Processing, optimal for reducing unstable value fluctuations due to interference by maintaining accurate readings. Therefore it often used signal coding context of time (Smith, 1999). kind moving average Exponentially Weighted (EWMA) which applied a sequence random variables, calculating weighted applying weight that decreases geometrically with length observation (Perry, 2011). this can be tools/instruments use data continuously certain so will require are not extreme result changes output response being softer as damage device on output. This study uses EWMA eliminate noise processing sensor results study, system able monitor realtime ph and temperature data. In fish farming, measuring monitoring water important, if regularly measured monitored cause various problems such pH growth health. research carried out R&D, multi-sensor circuit then processed logger displayed serial its