Design of FTTS forecasting model using Markov chain and P2AMF framework case study: Farmer's Terms of Trade of Smallholders Estate Crops Subsector in Riau

Abstract

Precise and accurate data of Farmer's Terms of Trade of Smallholders Estate Crops Subsector (FTTS) are needed by government to be used as a recommendation to make decision and policy in the future. However, delay in provision of FTTS becomes obstacle for government. In this research, it will be designed forecasting model of FTTS using Markov chain and Predictive, Probabilistic Architecture Modeling Framework (P2AMF). It will be compared with forecasting model of FTTS using Autoregressive Integrated Moving Average (ARIMA). The first experiment and the second experiment show that Markov chain method is better than ARIMA method. It can be proven by Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Both MSE and MAPE of Markov chain method are smaller than those of ARIMA method. In the first experiment, MSE and MAPE of Markov chain method are 251.0386 and 0.1548 respectively, whereas MSE and MAPE of ARIMA method are 283.4389 and 0.1570 respectively. In the second experiment, MSE and MAPE of Markov chain method are 2.3954 and 0.0133 respectively, whereas MSE and MAPE of ARIMA method are 5.8713 and 0.0191 respectively.