The time series forecasting method is a forecast that relies on quantitative past data to create a forecasting process, and it is an interesting forecasting method for developing forecasting efficiency due to various factors that will result in better forecasting process accuracy. In the forecasting process, forecasters must determine the accuracy of forecasting methods before applying them by measuring forecast errors. It is measured by the difference between the forecasted values and the actual values. The method of error measurement is also an appropriate consideration to be used to make decisions on choosing effective forecasting methods. Therefore, this research presented in the first part of the article also aims to present a literature review of the relevant topic of error measurement in the forecasting method. In the second part of the article, to identify research gaps in the relevant literature review, it was found that the error measurement of the forecasting method had more than one error measurement method. The results of each error are contradictory, or the results are not in the same direction. This made it difficult to decide on a forecasting method to use. This is a research gap and led to the introduction of a conceptual model for developing a selection error measurement method to measure the effectiveness of the time series forecasting method. This results in the accuracy of the chosen forecasting method. The researcher has set the structure of the research method to be used as a research process and will be presenting research results in the future.