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All Journal JURNAL RISET AKUNTANSI JAMBI Khazanah Intelektual
Gusmanely.Z
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Agriculture, Biological Sciences & Forestry Humanities Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education

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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.
Implementasi Metode Exponensial Smooting dalam Memprediksi Harga Logam Mulia Emas Optimasi Abadi (Eoa Gold) Gusmanely.Z; Gusmanley; Corry Sormin
JURNAL RISET AKUNTANSI JAMBI Vol. 6 No. 1 (2023): JURNAL RISET AKUNTANSI JAMBI
Publisher : LPPM Universitas Adiwangsa Jambi

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

Abstract

Precious metals are one of the best investment choices and are currently still the prima donna in people's lives. The development of the times has caused precious metals, especially bars, to appear with various brands, one of which is Eoa Gold, which has advantages over other LMs. The price of precious metals always changes from time to time and the demand for it in Indonesia is increasing, so one solution is needed, namely forecasting Gold prices in Indonesia. This aims to find out the price of precious metals that will come. The forecasting method in this study uses the Single Exponential Smoothing method which can perfect a forecasting result by smoothing past values which function to produce forecasting values. The data used is time series data from January 1 2022 to December 31 2022 for 12 months. Then, in this study, the SES analysis uses the parameters dan ,, then evaluates the error value of the forecasting results with the Mean Absolute Percentage Error (MAPE). The lowest MAPE results obtained were when the parameter for all Eoa Gold sizes with values of 0,44%, 0,43%, 3,74% and 0,51%. Based on the MAPE value criteria, it is concluded that the Single exponential smoothing method is very accurate in forecasting the price of Eoa Gold.
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.
Co-Authors Corry Sormin Gusmanley Nurhafisah Sufri Sufri