Forecasting Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES)

Currently, Gorontalo Province is experiencing the problem of unstable rice prices from the government which makes it difficult for people to meet their food needs, especially rice. There are several factors that can influence rice price instability, namely high demand from other regions, large areas of harvested land, and weather conditions such as drought, floods and the spread of pests that can destroy rice plants. This can cause the price of rice to increase and decrease each month. Therefore, forecasting rice prices for the future is carried out. The method used to forecast is hybrid Singular Spectrum Analysis and Triple Exponential Smoothing. The criteria for determining forecasting accuracy are based on the Mean Absolute Percentage Error value. After the forecasting was carried out, the hybrid Singular Spectrum Analysis and Triple Exponential Smoothing forecasting obtained a Mean Absolute Percentage Error (MAPE) value of 0.04352537 or 4.35%. The hybrid method of Singular Spectrum Analysis and Triple Exponential Smoothing is said to be better if it has an accuracy value of less than 10%.

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Publication Details

Journal
Jurnal Matematika Statistika dan Komputasi
Published
2025-09-08
DOI
https://doi.org/10.20956/j.v22i1.43322
Primary Topic
Statistical and numerical algorithms
Type
article
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article

Forecasting Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES)

Ismail Djakaria, Armayani Arsal, Lisnawati R. Hunowu
Jurnal Matematika Statistika dan Komputasi
Statistical and numerical algorithms
article

Forecasting Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES)

Ismail Djakaria, Armayani Arsal, Lisnawati R. Hunowu
article en

Abstract

Currently, Gorontalo Province is experiencing the problem of unstable rice prices from the government which makes it difficult for people to meet their food needs, especially rice. There are several factors that can influence rice price instability, namely high demand from other regions, large areas of harvested land, and weather conditions such as drought, floods and the spread of pests that can destroy rice plants. This can cause the price of rice to increase and decrease each month. Therefore, forecasting rice prices for the future is carried out. The method used to forecast is hybrid Singular Spectrum Analysis and Triple Exponential Smoothing. The criteria for determining forecasting accuracy are based on the Mean Absolute Percentage Error value. After the forecasting was carried out, the hybrid Singular Spectrum Analysis and Triple Exponential Smoothing forecasting obtained a Mean Absolute Percentage Error (MAPE) value of 0.04352537 or 4.35%. The hybrid method of Singular Spectrum Analysis and Triple Exponential Smoothing is said to be better if it has an accuracy value of less than 10%.

Jurnal Matematika Statistika dan KomputasiVol. 22(1)
Openalex Percentile: Top 64%
Statistical and numerical algorithms
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Forecasting Rice Prices in Gorontalo Province Using Hybrid Singular Spectrum Analysis (SSA) and Triple Exponential Smoothing Methods (TES) — Ismail Djakaria, Armayani Arsal, et al. · Jurnal Matematika Statistika dan Komputasi (2025) | TGRS Research Map | TGRS