Forecasting Farmer Exchange Rate (FER) in Southeast Sulawesi Province Using Cheng’s Fuzzy Time Series Method - Rastina; Lilis Laome; Bahriddin Abapihi; Gusti Ngurah Adhi Wibawa; Mukhsar Laome; Makkulau Laome; Gama Putra Danu Sohibien; Sukim; Fathurrahman Yahyasatrio (Jurnal Aplikasi Statistika & Komputasi Statistik, 2025)
Introduction/Main Objectives: This study aims to forecast the Farmer Exchange Rate (FER) in Southeast Sulawesi Province for 2024 as a basis for short-term economic assessment and policy-related analysis. Background Problems: FER is a key indicator of farmers’ purchasing power and agricultural welfare; however, its monthly dynamics are characterized by fluctuations and uncertainty, making conventional forecasting methods less effective in capturing its behavior. Novelty: This study contributes by implementing the the Fuzzy Time Series (FTS) Cheng approach for FER forecasting in Southeast Sulawesi, emphasizing its suitability for handling vagueness and nonlinear patterns inherent in agricultural economic indicators. Research Methods: The analysis utilizes monthly secondary FER data obtained from BPS-Statistics of Southeast Sulawesi Province, covering the period from January 2014 to December 2023. Forecast accuracy is evaluated using the Mean Absolute Percentage Error (MAPE). Finding/Results: The forecasting results indicate that the FER values for January, February, and March 2024 are each estimated at 105.93. The model achieved a MAPE of 0.3027%, corresponding to an accuracy level of 99.6973%, which places the forecasting performance in the “excellent” category.