Red Curly Chili Forecast in Southeast Sulawesi Using Auto Regressive Integrated Moving Average (ARIMA)

Abstract. Price is a crucial aspect in the world of trade. Red curly chili peppers have become one of the plants favored by many consumers. This research aims to develop a forecasting model that can provide a more accurate insight into the future prices of red chili peppers, particularly in Southeast Sulawesi. Because price forecasting plays a crucial role in predicting future price trends, the Auto Regressive Integrated Moving Average (ARIMA) method becomes one of the models that can be used for time series analysis. The data for this research is sourced from the National Food Body Price Panel Website. The data period starts from August 8, 2022, to December 15, 2023, with the last 500 days' prices used as both test and training data. In this study, the ARIMA (1,1,1) model emerged as the best among the three ARIMA models analyzed. The ARIMA (1,1,1) model yielded a MAPE percentage of 17.97%, indicating that this model is suitable or reliable for time series forecasting. Furthermore, the results of this experiment show that the forecasted prices for the next 10 days do not experience significant decreases or increases, referring to several recent data points used as training data samples.

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Publication Details

Journal
Jurnal CoreIT Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi
Published
2025-07-15
DOI
https://doi.org/10.24014/coreit.v11i1.33986
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Red Curly Chili Forecast in Southeast Sulawesi Using Auto Regressive Integrated Moving Average (ARIMA)

Jurnal CoreIT Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi
Geochemistry and Geologic Mapping
article

Red Curly Chili Forecast in Southeast Sulawesi Using Auto Regressive Integrated Moving Average (ARIMA)

article en

Abstract

Abstract. Price is a crucial aspect in the world of trade. Red curly chili peppers have become one of the plants favored by many consumers. This research aims to develop a forecasting model that can provide a more accurate insight into the future prices of red chili peppers, particularly in Southeast Sulawesi. Because price forecasting plays a crucial role in predicting future price trends, the Auto Regressive Integrated Moving Average (ARIMA) method becomes one of the models that can be used for time series analysis. The data for this research is sourced from the National Food Body Price Panel Website. The data period starts from August 8, 2022, to December 15, 2023, with the last 500 days' prices used as both test and training data. In this study, the ARIMA (1,1,1) model emerged as the best among the three ARIMA models analyzed. The ARIMA (1,1,1) model yielded a MAPE percentage of 17.97%, indicating that this model is suitable or reliable for time series forecasting. Furthermore, the results of this experiment show that the forecasted prices for the next 10 days do not experience significant decreases or increases, referring to several recent data points used as training data samples.

Jurnal CoreIT Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi InformasiVol. 11(1)
Universitas Halu Oleo (ID)
Zero hunger
Openalex Percentile: Top 27%
Geochemistry and Geologic Mapping
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Red Curly Chili Forecast in Southeast Sulawesi Using Auto Regressive Integrated Moving Average (ARIMA) · Jurnal CoreIT Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi (2025) | TGRS Research Map | TGRS