Phatsa: A web-based application for forecasting using conventional moving average methods

Abstract

Forecasting with time series was made by hypothetical study that historical data related with the future data. Moving average (MA) is one of the well-known methods to be used in forecasting technique. Although there are several methods that already developed like soft computing and modified methods, conventional moving average methods still implemented in recent researches because of its simplicity. This study conducts a development of web-based application called Phatsa (PHP Application for Time Series Analysis) that implements three conventional moving average methods, i.e. the SMA, WMA and EMA. All the calculation tested in 100–5000 rows of time series dataset with the maximum calculating time below 0.4 seconds. Calculating time is relatively linear with the complexity of its equation, EMA has the biggest amount of time while SMA has the lowest one.