Modeling Cabbage Production in Malang East Java with GSTAR Approach

EasyChair Preprint no. 4663

Abstract

Based on the Directorate Report General's Horticulture, the contribution of vegetable horticulture agriculture tends to increase, where the GDP of vegetable horticulture has increased by 9.86%. In 2016, cabbage is a vegetable horticultural commodity that has the highest production amount in Indonesia, and the poor district is one of the major producers of commodities cabbage in eastern Java. Generalized Space-Time Autoregressive (GSTAR) is a multivariate time series model that considers site aspects with heterogeneous location characteristics. The purpose of this study was to model cabbage production in Malang Regency using the GSTAR model. Selection criteria for the best model to use the value of the root mean square error (RMSE) and the value of R^2. The results showed that the GSTAR model (1,2) is the best model for modeling cabbage production and has good forecasting accuracy to predict cabbage production in Malang Regency.

Keyphrases: Generalized Space-Time Autoregressive (GSTAR) Cabbage, R2, Root Mean Square Error (RMSE)

@Booklet{EasyChair:4663,
  author = {Muhammad Syahfitra and Ni Wayan S. Wardhani and Atiek Iriany},
  title = {Modeling Cabbage Production in Malang East Java with GSTAR Approach},
  howpublished = {EasyChair Preprint no. 4663},

  year = {EasyChair, 2020}}