Forecasting Model of Agriculture Commodity of Value Export of Coffee; Application of Arima Model

Erlina, Rr.; Azhar, Rialdi

doi:10.23960/jtep-l.v9i3.257-263

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Besides,

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models consider as reference model in time series forecasting. This model use to forecast corn production Ilić et al (2016) and the agricultural commodity value of coffee Erlina and Rialdi (2020). These researches contribute to the understanding of agriculture indices dynamics and aids in decision‐making processes related to agricultural planning and resource allocation.…”

Section: Related Work In Agricultural Forecasting and Application Of ...mentioning

confidence: 99%

Forecasting agricultures security indices: Evidence from transformers method

Bilel

2024

Journal of Forecasting

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In recent years, ensuring food security has become a global concern, necessitating accurate forecasting of agriculture security to aid in policymaking and resource allocation. This article proposes the utilization of transformers, a powerful deep learning technique, for predicting the Agriculture Security Index ( ). The is a comprehensive metric that evaluates the stability and resilience of agricultural systems. By harnessing the temporal dependencies and complex patterns present in historical data, transformers offer a promising approach for accurate and reliable forecasting. The transformer architecture, renowned for its ability to capture long‐range dependencies, is tailored to suit the forecasting task. The model is trained using a combination of supervised learning and attention mechanisms to identify salient features and capture intricate relationships within the data. To evaluate the performance of the proposed method, various evaluation metrics, including mean absolute error, root mean square error, and coefficient of determination, are employed to assess the accuracy, robustness, and generalizability of the transformer‐based forecasting approach. The results obtained demonstrate the efficacy of transformers in forecasting the , outperforming traditional time series forecasting methods. The transformer model showcases its ability to capture both short‐term fluctuations and long‐term trends in the , allowing policymakers and stakeholders to make informed decisions. Additionally, the study identifies key factors that significantly influence agriculture security, providing valuable insights for proactive intervention and resource allocation.

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“…Besides,

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Section: Related Work In Agricultural Forecasting and Application Of ...mentioning

confidence: 99%

Forecasting agricultures security indices: Evidence from transformers method

Bilel

2024

Journal of Forecasting

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“…Mereka memprediksi pendapatan negara Sri Langka yang berasal dari ekspor lada. Peramalan ekspor kopi dilakukan oleh Erlina & Azhar (2020). Kim (2018) meneliti nilai ekspor di Korea sebelum dan sesudah krisis keuangan global dengan menggabungkan model ARIMA dan EGARCH.…”

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Peramalan Ekspor Karet Provinsi Jambi dengan Model Seasonal ARIMA

Atmanegara

2022

JIITUJ

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The industrial sector contributed the most to total non-oil and gas exports in Jambi Province. Rubber and its processed products are the main export commodities in the industrial sector. The export value of rubber and its products increased in 2017 but decreased again from 2018 to 2020. The decline in exports harmed the economy in Jambi Province. It is necessary to predict the export value of rubber and its products in the coming period. Forecasting is done on time series data using the ARIMA and SARIMA models. The best model for modeling the export value of rubber and its products in Jambi Province is SARIMA (0,1,1)(0,0,1)12. It is predicted that the export value of rubber and its processed products will decrease by around 4 percent in 2022. And decrease by around 5 percent in 2023. The results of this forecast can be used as an early warning in making policies related to exports in the coming period.

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“…Previous research only forecast Indonesian coffee exports in the international market (Chandra et al, 2013;Erlina & Azhar, 2020;Hamzah et al, 2020). Their research shows that Indonesia's coffee exports are predicted to increase.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the fluctuating export volume, it is predicted that the Indonesian coffee export value will increase (Erlina & Azhar, 2020). The export volume of Robusta coffee, one of the types of coffee exported by Indonesia, is also forecast to experience an annual 1.6 percent increase, even though Robusta is considered the second-class coffee with quality that is less able to compete in the international market (Chandra et al, 2013;Sahat et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Forecasting Export Volume of Indonesian and Colombian Coffee in the World Market using ARIMA Model

Zuhdi¹,

Maulana

Rambe

2023

Signifikan

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Colombian coffee exports influence Indonesian coffee exports in the short term, so this study aims to forecast the export volume of Indonesian and Colombian coffee in the future. The study used time-series data from 2001 to 2021, further analyzed using the ARIMA model. Based on the projection, Indonesian coffee export is projected to increase with an average value of 1.14 percent and a potential increase of 1.79 percent. However, this result still needed to reach the desired value since the projected coffee export of Indonesia in 2025 only reached 429 172 tons, or lower than the export quantity of Colombian coffee in 2011. This finding indicated that Indonesian coffee export tended to increase stagnantly and was considered low compared to the increasing export of Colombian coffee.JEL Classification: C22, C53, E37, F17, Q13How to Cite:Zuhdi, F., Maulana A. S., & Rambe, K. R. (2023). Forecasting Export Volume of Indonesian and Colombian Coffee in the World Market using ARIMA Model. Signifikan: Jurnal Ilmu Ekonomi, 12(1), 57-68. https://doi.org/10.15408/sjie.v12i1.25456.

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Forecasting Model of Agriculture Commodity of Value Export of Coffee; Application of Arima Model

Cited by 7 publications

References 8 publications

Forecasting agricultures security indices: Evidence from transformers method

Forecasting agricultures security indices: Evidence from transformers method

Peramalan Ekspor Karet Provinsi Jambi dengan Model Seasonal ARIMA

Forecasting Export Volume of Indonesian and Colombian Coffee in the World Market using ARIMA Model

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