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PENGGUNAAN MODEL SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) DALAM MEMPREDIKSI JUMLAH CURAH HUJAN DI KABUPATEN MUARO JAMBI TAHUN 2024 Nurhafisah; Gusmanely.Z; Sufri
Jurnal Khazanah Intelektual Vol. 8 No. 1 (2024): Khazanah Intelektual
Publisher : Balitbangda Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37250/khazanah.v8i1.237

Abstract

Rain is a source of water where water is an important element in life, one of which is in the agricultural sector. High rainfall can cause floods which cause damage to agricultural crops so that farmers will experience crop failure. In 2021, 2,591 hectares of rice fields in Muaro Jambi Regency experienced crop failure due to flooding caused by high rainfall. This is an important reason to predict the amount of rainfall in Muaro Jambi Regency so that it can help in making decisions to anticipate crop failure. Rainfall is often difficult to predict, so it is necessary to identify data patterns to determine the appropriate method and determine the best model that can be used to predict the amount of rainfall in Muaro Jambi Regency. The results of identifying rainfall data patterns in Muaro Jambi Regency show that the rainfall data in Muaro Jambi Regency contains seasonal patterns. SARIMA is a forecasting method that is suitable for application to data that contains seasonal patterns. The best model that can be used to predict the amount of rainfall in Muaro Jambi Regency is the SARIMA(1,0,0)(1,0,0)12 model with forecasting accuracy classified as very good with a MAPE value of 0.05041% and an MSE of 8959 .8 which is obtained from calculating the error value between the actual data and the forecast results on outsample data.
PENGGUNAAN MODEL SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) DALAM MEMPREDIKSI JUMLAH CURAH HUJAN DI KABUPATEN MUARO JAMBI TAHUN 2024 Nurhafisah; Gusmanely.Z; Sufri
Jurnal Khazanah Intelektual Vol. 8 No. 1 (2024): Khazanah Intelektual
Publisher : Brida Provinsi Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37250/khazanah.v8i1.237

Abstract

Rain is a source of water where water is an important element in life, one of which is in the agricultural sector. High rainfall can cause floods which cause damage to agricultural crops so that farmers will experience crop failure. In 2021, 2,591 hectares of rice fields in Muaro Jambi Regency experienced crop failure due to flooding caused by high rainfall. This is an important reason to predict the amount of rainfall in Muaro Jambi Regency so that it can help in making decisions to anticipate crop failure. Rainfall is often difficult to predict, so it is necessary to identify data patterns to determine the appropriate method and determine the best model that can be used to predict the amount of rainfall in Muaro Jambi Regency. The results of identifying rainfall data patterns in Muaro Jambi Regency show that the rainfall data in Muaro Jambi Regency contains seasonal patterns. SARIMA is a forecasting method that is suitable for application to data that contains seasonal patterns. The best model that can be used to predict the amount of rainfall in Muaro Jambi Regency is the SARIMA(1,0,0)(1,0,0)12 model with forecasting accuracy classified as very good with a MAPE value of 0.05041% and an MSE of 8959 .8 which is obtained from calculating the error value between the actual data and the forecast results on outsample data.