Open AccessModeling of red onion production in Central Java using hybrid ARIMA-ANFIS
Author(s) -
Inas Husna Diarsih,
Tarno,
Agus Rusgiyono
Publication year - 2019
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 - 10.1088/1742-6596/1217/1/012080
Subject(s) - autoregressive integrated moving average , adaptive neuro fuzzy inference system , production (economics) , mean squared error , java , mathematics , statistics , computer science , fuzzy logic , time series , economics , artificial intelligence , fuzzy control system , macroeconomics , programming language
Red onion is one of the strategic horticulture commodities in Indonesia considering its function as the main ingredients of the basic ingredients of Indonesian food. For increasing production to supply national necessary, Central Java as the main center of red onion production should be able to predict the production of several periods to maintain the balance of national production. The purpose of this research is to get the best model to forecast the production of red onion in Central Java by ARIMA, ANFIS, and hybrid ARIMA-ANFIS method. The smallest RMSE and AIC values measure model accuracy. The results show that the best model for modeling red onion production in Central Java is obtained by hybrid ARIMA - ANFIS model which is a combination between SARIMA ([2], 1, [12]) and residual ARIMA using ANFIS model with input e t,1 , e t,2 on the grid partition technique, gbell membership function, and membership number of 2 that produce RMSE 12033 and AIC 21.6634. While ARIMA model yield RMSE 13301,24 and AIC 21,89807 with violation of assumption. And the ANFIS model produces RMSE 14832 and AIC 22,0777. It shows that ARIMA-ANFIS hybrid method is better than ARIMA and ANFIS.