Can Paddy Growing Phase Produce an Accurate Forecast of Paddy Harvested Area in Indonesia? Analysis of the Area Sampling Frame Results

Kadir Ruslan, Octavia Rizky Prasetyo
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Abstract

Our study aims to evaluate the accuracy of the forecasts produced based on the paddy growing phase obtained from the results of the Area Sampling Frame (ASF) Survey and, as a comparison, proposes an alternative forecast method taking into account the seasonal pattern and hierarchical structure of the national paddy harvested area estimation obtained from the ASF to improve the accuracy. In doing so, we calculated the MAPE by comparing the realization of paddy harvested area during the period January to September 2022 with their forecasts produced from the area of generative, late vegetative, and early vegetative phases. We also implemented a Hierarchical forecasting method on monthly data of the harvested area from January 2018 to August 2022 for all provinces. Specifically, we applied the bottom-up method for the reconciliation and the rolling window method to produce a three-consecutive month forecast for the period January to September 2022. We found that the accuracy prediction based on the paddy growing phase is moderately accurate. The combination of the bottom-up reconciliation method and the SARIMA model produces a much better accuracy for the national figure of paddy harvested area as shown by a lower MAPE. Our findings suggest that the Hierarchical forecasting method could be an alternative for the prediction of harvested area based on the ASF results other than the prediction obtained from the standing crops.
水稻生长阶段能否准确预测印度尼西亚的水稻收获面积?面积抽样框架结果分析
我们的研究旨在评估根据面积抽样框架(ASF)调查结果得出的水稻生长阶段预测结果的准确性,作为比较,我们提出了一种替代预测方法,该方法考虑了从面积抽样框架中获得的全国水稻收获面积估算结果的季节模式和层次结构,以提高准确性。为此,我们通过比较 2022 年 1 月至 9 月期间水稻收获面积的实现情况及其从生成期、植期后期和植期早期得出的预测结果,计算了 MAPE。我们还对 2018 年 1 月至 2022 年 8 月各省的月度收割面积数据实施了层次预测法。具体而言,我们采用自下而上法进行调和,并采用滚动窗口法对 2022 年 1 月至 9 月进行连续三个月的预测。我们发现,基于水稻生长阶段的精度预测准确度适中。自下而上的调和方法与 SARIMA 模型相结合,对全国水稻收获面积的预测准确度更高,MAPE 更低。我们的研究结果表明,分层预测法可以作为根据 ASF 结果预测收获面积的替代方法,而不是根据立枯丝核算得出的预测结果。
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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