Comparison of Fuzzy Time Series Chen and Cheng to Forecast Indonesia Rice Productivity

Abstract

Based on BPS data in 2019, around 90% of Indonesians consume rice as the main product of their carbohydrate needs. With the fourth most populous country in the world, Indonesia's rice consumption in 2021 will reach 31.50 million tons. Indonesia's rice production is currently not able to supply the needs of domestic rice consumption. Therefore, the Indonesian government chose to import rice for supply the needs of domestic rice consumption. Forecasting method can help the government to reduce uncertainty about the future of rice productivity. This research will discuss the comparison of the forecasting results of fuzzy timeseries using chen and cheng models in forecasting rice productivity in Indonesia. The comparison based on the percentage of eror or in this research the MAPE value is used as an indicator. The MAPE value obtained using chen model is 18% and using cheng model is 12%. The result of data analysis found that the MAPE value using cheng model is smaller than using chen model. It means that the cheng model is more appropriate used in forecasting data of Indonesia productivity rice. However the chen and cheng models both give good forecasting result because the MAPE value is less than 20%