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All Journal Economic Journal of Emerging Markets Al-Fath Jurnal Komputer, Informasi dan Teknologi Kohesi: Jurnal Sains dan Teknologi Cendikia Pendidikan Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Akhlak: Jurnal Pendidikan Agama Islam Dan Filsafat Pelayanan Unggulan: Jurnal Pengabdian Masyarakat Terapan Educational Dynamics: International Journal of Education and Social Sciences RAGAM: Journal of Statistics and Its Application
Khairullah Khairullah
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Mathematics Physics Public Health Social Sciences Other

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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
RAGAM: Journal of Statistics & Its Application Vol 2, No 2 (2023): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v2i2.11334

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
Co-Authors Armadhan Syarif Hidayat Bagus Tri Putra Dandy Sunardi Erwan Yusuf Ghepri Haikal Giova Giova Gusti Hadiatus Solehah Harry Witriyono Harry Witriyono Malik Cahyadin Muhammad Arbain Muhammad Ardiansah Putra Nabila Septiani Nur Salam Wahyu Dharma Putra Yuza Reswan