Modeling Cabbage Production in Malang East Java with GSTAR Approach

Muhammad Syahfitra, N. W. S. Wardhani, A. Iriany
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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 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.
用GSTAR方法模拟东爪哇玛琅白菜生产
根据总局园艺报告,蔬菜园艺农业的贡献有增加的趋势,其中蔬菜园艺的GDP增长了9.86%。2016年,卷心菜是印尼产量最高的蔬菜园艺商品,贫困地区是爪哇东部商品卷心菜的主要生产地之一。广义时空自回归(GSTAR)模型是一种考虑具有异质区位特征的场地方面的多元时间序列模型。本研究的目的是利用GSTAR模型对玛琅县的白菜生产进行建模。采用均方根误差(RMSE)值和R值作为最佳模型的选择标准。结果表明,GSTAR模型(1,2)是模拟大白菜产量的最佳模型,对麻郎地区大白菜产量有较好的预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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