Forecasting Indonesia's Unemployment Rates Using Moving Average Methods

Mira Orisa‬(1), Ahmad Faisol(2),


(1) Institut Teknologi Nasional Malang
(2) Institut Teknologi Nasional Malang)

Abstract


In general, individuals with higher levels of education tend to have more opportunities for better workplace employment. Unemployment stands as one of the major social and economic issues in Indonesia. Forecasting can aid governments in predicting the annual unemployment rate. One of the methods used for forecasting is the simple moving average. This method is advantageous over other forecasting techniques when processing data with less complex fluctuations. It is utilized to align historical data over a specific time frame to identify underlying trends or patterns in the data. The moving average method involves two crucial stages: selecting the time window and evenly calculating the values within that window. Based on the data decomposition results, two time periods were identified within the dataset: one spanning 6 months and the other 12 months. The mean absolute percentage error (MAPE) associated with the 6-month Period is lower than that of the 12-month window, indicating that predictions derived from a 6-month timeframe are more accurate than those based on a 12-month period. A clear relationship is observed between the volume of data (number of observations) and the accuracy of predictions for the simple moving average.

Keywords


Forecasting; Moving Average; MAPE; Unemployment

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References


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