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All Journal Journal of Statistics and Data Science
Putriasari, Novi
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other

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Journal : journal of statistics and data science

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Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21007

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is anecessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is a necessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA K (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
Co-Authors Agwil, Winalia Ramya Rachmawati Sigit Nugroho Sitohang, Yosep O