Modeling Cabbage Production in Malang East Java with GSTAR Approach

DOI

10.2991/assehr.k.210508.078How to use a DOI?

Keywords

Generalized Space-Time Autoregressive (GSTAR), Cabbage, root mean square error (RMSE), R2

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 R2. 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.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Muhammad Syahfitra
AU  - Ni Wayan S. Wardhani
AU  - Atiek Iriany
PY  - 2021
DA  - 2021/05/11
TI  - Modeling Cabbage Production in Malang East Java with GSTAR Approach
BT  - Proceedings of the 1st International Conference on Mathematics and Mathematics Education (ICMMEd 2020)
PB  - Atlantis Press
SP  - 299
EP  - 303
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210508.078
DO  - 10.2991/assehr.k.210508.078
ID  - Syahfitra2021
ER  -