实施向量自回归法预测巴东县的水稻产量

Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Pub Date : 2024-03-30 DOI:10.36312/jcm.v5i1.2122

Margaretha Ratih Dyah Novitasari, I Wayan Sumarjaya, I Gusti Ayu Made Srinadi

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引用次数: 0

摘要

预测是利用过去的数据对未来事物进行预测的过程。预测中常用的模型之一是时间序列数据，即向量自回归（VAR）模型。研究的目的是了解巴东县水稻生产的模型和数量。研究使用了从巴厘岛 BPS 办事处和登巴萨 BMKG 获取的次级数据，即从 2018 年 1 月至 2022 年 12 月的水稻产量数据、收获面积和降雨量。根据滞后最优模型 VAR，研究结果表明 VAR(1) 模型适合使用。因此，根据 MAPE 预测标准，本研究中的 VAR 模型显示结果不太准确。尽管水稻产量、收获面积和降雨量的预测模式显示出稳定性。此外，在第一期的 IRF 分析中出现了震荡，但最终达到了稳定状态。关键词预测 VAR 模型水稻产量收获面积降水量

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IMPLEMENTASI METODE VECTOR AUTOREGRESSIVE DALAM PERAMALAN JUMLAH PRODUKSI PADI DI KABUPATEN BADUNG

Forecast is a process to predict something in the future using past data. One of common model used in forecast is time series data that is vector autoregressive (VAR) model. The research purpose is to know the model and amount of rice production in Badung regency. It is used seconder data get from the BPS office Bali and BMKG Denpasar, that are rice production data, harvest area, and rainfall from Januari 2018 till December 2022. Base on lag optimum model VAR, the research result show that the VAR(1) model is suitable being used. Therefore, base on MAPE forecast criteria the VAR model in this research show the result less accurate. Eventhough the forecast pattern for rice production, harvest area, and rainfall show the stability. Beside that in the first period there is shocking in the IRF analysis but finally reach the stabil condition. Keywords: Forecast, VAR models, Rice Production, Harvest Area, Rainfall

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Jurnal Cahaya Mandalika ISSN 2721-4796 (online)

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