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All Journal Panrannuangku Jurnal Pengabdian Masyarakat Saraq Opat : Jurnal Administrasi Publik Innovative: Journal Of Social Science Research Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Journal of Mathematics, Computation and Statistics (JMATHCOS)
Rahman, Muhammad Fatur
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Humanities Computer Science & IT Education Engineering Health Professions Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

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Journal : Journal of Mathematics, Computation and Statistics (JMATHCOS)

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Generalized Space-Time Autoregressive Moving Average Model with Rainfall as Exogenous Variable for Inflation Data in Sulawesi Island Rahman, Muhammad Fatur; Ihsan, Hisyam; Sanusi, Wahidah
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.8798

Abstract

The Generalized Space-Time Autoregressive Moving Average with Exogenous Variables (GSTARMAX) model is an extension of the Generalized Space-Time Autoregressive Moving Average (GSTARMA) model, incorporating an exogenous variable (X) to enhance model accuracy while accounting for external factors. The advantage of the GSTARMAX model is its ability to accommodate location heterogeneity and generate a picture of an event for several future periods while considering other factors outside the scope of observation. This study applies the GSTARMAX model approach to analyze inflation data in Sulawesi Island, considering rainfall as an exogenous variable. Given the extreme and unpredictable climate changes, particularly rainfall in the Sulawesi region, which have become an annual phenomenon in recent years. This not only impacts community activities but also triggers uncertainty in future inflation. Uncontrolled inflation affects the decline in purchasing power, increases production costs, and disrupts goods distribution. Therefore, the objective of this study is to develop a model that can describe inflation in Sulawesi Island based on historical inflation and rainfall data. This study discusses the application of the Generalized Space-Time Autoregressive Moving Average with Exogenous Variables (GSTARMAX) model to analyze inflation in Sulawesi Island during the period 2020-2024. The data collected are from six provinces in Sulawesi Island: South Sulawesi, Southeast Sulawesi, West Sulawesi, Central Sulawesi, North Sulawesi, and Gorontalo. This study uses inverse distance weighting and cross-correlation normalization to build the model. The results indicate that the GSTARMAX (11;0;0) (1;2;0) or GSTARX (11) (1;2;0) model using cross-correlation normalization weights is the best model for inflation data in Sulawesi Island, with residuals that meet the white noise assumption. This means the model can be used to forecast future inflation.
Co-Authors Ahmad Zaki Ahmar, Ansari Saleh Andita, Citra Ardelia, Fatina Armasari, Fanny Darma, Sidrah Djam'an, Nurwati Fajar Arwadi Gani, Aziz Beru Hisyam Ihsan Irwan Irwan Junaidi, Dita Rahmaditiani Lestari, Nur Ayu Mawar Mawar, Mawar Muhammad Farhan Mutmainnah MR, Luthfiah Purnamasari, Reeny Safitri N.N, Novi Sidjara, Sahlan Sutamrin Syafruddin Side Wahidah Sanusi