Peramalam Garis Kemiskinan menggunakan Metode Double Moving Average di Provinsi Sumatera Barat - Nugraha Rahmansyah; Shary Armonitha Lusinia; Rima Liana Gema; Silky Safira (Universitas Putra Indonesia YPTK Padang, 2021)
Forecasting methods can predict the values ​​of a variable based on the known value of that variable or other related variables. In the quantitative category forecasting method, especially the time series model, several smoothing methods are known, namely average and exponential smoothing. A trended series is defined as a time series that contains a long-term component that represents growth or decline in the series, and whose average value changes up or down over a period of time. The average method is that a number of values ​​that are given an equivalent weight (or smoothed) are included in the calculation of the average. A double moving average, also known as a linear moving average, is designed for time series data with a trending pattern or a linear trend. The time series data used is poverty line data by area of ​​residence in West Sumatra based on the ability to meet basic needs (basic needs approach). With this approach, poverty is seen as an economic inability to meet basic food and non-food needs as measured from the expenditure side. So the poor are people who have an average monthly per capita expenditure below the poverty line. So that the double moving average time series method is used. This study aims to determine the monthly per capita public expenditure forecast in West Sumatra.