Forecasting Farmers' Exchange Rates in North Sumatra Using the Arima Method

Abstract

This study aims to forecast the farmer exchange rate (Nilai Tukar Petani, NTP) in North Sumatra in 2024 using the ARIMA method. The main objective of this study is to obtain a forecasting model that can be used to predict the farmer exchange rate over a certain time horizon and to measure the accuracy of the model through MAPE (Mean Absolute Percentage Error) analysis. The methodology used in this study is time series analysis using the ARIMA (Autoregressive Integrated Moving Average) approach. The data used in this study are secondary data obtained from the Central Statistics Agency (BPS) of North Sumatra for the period 2019 to 2023. The forecasting results show that the most effective ARIMA model for predicting the NTP of North Sumatra is the ARIMA (0,1,1) model with MA(1). This model provides accurate forecasting results with a MAPE value of 96.7%, which falls into the category of highly feasible forecasting. In general, the forecasting results indicate fluctuations in NTP from 2019 to 2023, with predicted NTP for 2024 showing a decrease in certain months but an increase in others. These results provide useful insights for the government and farmers in planning better agricultural policies in the future