PRAKIRAAN INDEKS KEKERINGAN MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) BERDASARKAN DATA STANDARDIZED PRECIPITATION INDEX (SPI) KOTA BANJARBARU

Nabila Septiani, Nur Salam, Khairullah Khairullah

Abstract


Drought is a disaster that has a bad impact, especially in the city of Banjarbaru. There are  various ways to reduce the impact of drought in the future, one of which is by looking for information regarding the predicted drought index for the following year. The data used in this research to find the drought index value is Banjarbaru City rainfall data for 2007-2022. Seasonal Autoregressive Integrated Moving Average (SARIMA) method  is a calculated method for predicting rainfall data  and the data obtained is a forecast of rainfall in the city of Banjarbaru for the next 12 periods, namely SARIMA (0,2,3) (0,1,1)12. This model is a model that is suitable for use because it has fulfilled several tests, namely stationarity of variance and mean, significance test, white noise test and normality test with an AIC value of 1022,60 and an equation model obtained from SARIMA (0,2,3) (0,1,1)12 is (1-B)2 (1-B12) Zt=(1+1,77B-0,54B2+ 0,23B3 )(1-0,96B12 )εt. After obtaining forecast rainfall data for the next 12 periods. Rainfall data for 2007-2022 and forecast results for 2023 were used to find the drought index value using the Standardized Precipitation Index (SPI) method. It was found that the highest negative drought index value occurred in January, namely -1,774, including the dry category and the drought index had a positive value The highest occurred in June, namely 0,582, including the normal category.  The calculation results of this drought index forecast are used to provide additional information to anticipate drought disasters in the future.

 

Keywords:   Drought Index, Rainfall, SPI Method, SARIMA Method, AIC

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DOI: https://doi.org/10.20527/ragam.v2i2.11334

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RAGAM: Journal of Statistics and Its Application 

Program Studi Statistika, Fakultas MIPA, Universitas Lambung Mangkurat
Jalan A. Yani Km.36, Kampus ULM Banjarbaru, Kalimantan Selatan, Indonesia 70714

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RAGAM: Journal of Statistics and Its Application is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.