Arima Model for Forecasting Coffee Productivity in West Sumatra, Indonesia

As the 10th highest coffee-producing region in Indonesia, West Sumatra played a significant role in the country's coffee sector. Coffee productivity in West Sumatra had been fluctuating; therefore, accurate productivity forecasting was essential for effective coffee farm management, resource allocation, and market stability. This study aimed to identify the best forecasting model for predicting coffee productivity in West Sumatra from 2024 to 2028. The research method used was the descriptive analysis method, applying a time series forecasting approach. The data used in this study were historical records of coffee productivity in West Sumatra for the past 24 years. The data were annual figures from 2000 to 2023. The results showed that ARIMA (1,3,0) was the most suitable, with a Mean Absolute Percentage Error (MAPE) below 50%. This indicated a declining trend in coffee productivity over the forecast period. The projected productivity values (tons per hectare) were 1.000 in 2024, 0.6266 in 2025, 0.6125 in 2026, 0.0538 in 2027, and -0.1709 in 2028. The pattern of minor variations suggested that the ARIMA (1,3,0) model reflected an unstable and downward trend in coffee productivity.

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Publication Details

Journal
Indonesian Journal of Applied Research (IJAR)
Published
2025-08-29
DOI
https://doi.org/10.30997/ijar.v6i2.673
Primary Topic
Livestock Farming and Management
Type
article
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Arima Model for Forecasting Coffee Productivity in West Sumatra, Indonesia

Rusda Khairati, Vonny Indah Mutiara, Dwi Nur'aini Putri
Indonesian Journal of Applied Research (IJAR)
Livestock Farming and Management
article

Arima Model for Forecasting Coffee Productivity in West Sumatra, Indonesia

Rusda Khairati, Vonny Indah Mutiara, Dwi Nur'aini Putri
article en

Abstract

As the 10th highest coffee-producing region in Indonesia, West Sumatra played a significant role in the country's coffee sector. Coffee productivity in West Sumatra had been fluctuating; therefore, accurate productivity forecasting was essential for effective coffee farm management, resource allocation, and market stability. This study aimed to identify the best forecasting model for predicting coffee productivity in West Sumatra from 2024 to 2028. The research method used was the descriptive analysis method, applying a time series forecasting approach. The data used in this study were historical records of coffee productivity in West Sumatra for the past 24 years. The data were annual figures from 2000 to 2023. The results showed that ARIMA (1,3,0) was the most suitable, with a Mean Absolute Percentage Error (MAPE) below 50%. This indicated a declining trend in coffee productivity over the forecast period. The projected productivity values (tons per hectare) were 1.000 in 2024, 0.6266 in 2025, 0.6125 in 2026, 0.0538 in 2027, and -0.1709 in 2028. The pattern of minor variations suggested that the ARIMA (1,3,0) model reflected an unstable and downward trend in coffee productivity.

Indonesian Journal of Applied Research (IJAR)Vol. 6(2)
Andalas University (ID)
Openalex Percentile: Top 64%
Livestock Farming and Management
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Arima Model for Forecasting Coffee Productivity in West Sumatra, Indonesia — Rusda Khairati, Vonny Indah Mutiara, et al. · Indonesian Journal of Applied Research (IJAR) (2025) | TGRS Research Map | TGRS