Open AccessForecasting Farmer Exchange Rate in Bali Province Using Seasonal Autoregressive Integrated Moving Average (SARIMA) Method
Author(s) -
Dinda Pratiwi,
Sisilia Martina Utami Agustini,
Wiwin Windasari,
I Putu Eka Nila Kencana
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1503/1/012002
Subject(s) - autoregressive integrated moving average , purchasing power parity , price index , proxy (statistics) , agricultural economics , index (typography) , value (mathematics) , purchasing power , economics , agriculture , purchasing , exchange rate , geography , econometrics , agricultural science , mathematics , statistics , operations management , time series , environmental science , finance , computer science , archaeology , world wide web , keynesian economics
Farmer’s exchange rate (FER) is a proxy indicator to value the farmer’s purchasing rate and shows the term of trade between agricultural products and services sold and the goods purchased by farmers in producing and consuming households. FER obtained by comparing the Farmer Received Price Index with the Farmer Paid Price Index both expressed as percentages. The purpose of this study is to predict the FER of Bali Province from May 2019 to December 2019 and to count the level of purchasing power of the farmers. The monthly data of FER from January 2010 to April 2019 were used to build a seasonal ARIMA (SARIMA). Four models i.e. SARIMA(0, 1, 3), SARIMA(3,1, 0), SARIMA(4,1,0), and SARIMA(1,1, 1) with seasonal factor (0,1, 1) 12 were tested. Referring AIC value for SARIMA(0,1,3) as much as 326.94 is the lowest then we inferred this model is the best SARIMA model to predict the FER of Bali Province. Our research concludes the farmer’s income increases more than their expenditures.