Pemodelan Generalized Space Time Autoregressive untuk Meramalkan Data Inflasi Bulanan di Provinsi Jawa Barat

Hikma Abdia, Tiara Annisa Akhsan, Anisa Kalondeng, Siswanto Siswanto

Abstract


Inflation is the decline in the value of money due to the continuous increase in the value of goods and services. Inflation is also an economic phenomenon that greatly affects people's daily lives and the economic stability of a country. To maintain price stability and economic growth, it is important to monitor and forecast the inflation rate. The Generalized Space Time Autoregressive (GSTAR) method is a method that is able to forecast inflation rates involving interrelationships between location and time. The data used in this study is inflation data for 7 cities in West Java, namely Bandung, Bekasi, Bogor, Cirebon, Depok, Sukabumi and Tasikmalaya in January 2018 to December 2022. This purpose of this study is to obtain the best GSTAR model and forecasting results based on inflation data in seven cities in West Java. Based on the research results, the GSTAR ( model, the MSE value and MAPE value of the 80:20 which is 0.12% and 12.20%, and the forecast results obtained for six cities relatively increased and one city experienced a decline. So that the best model for inflation data of seven cities in West Java is the GSTAR (model with uniform location location weights.


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DOI: http://dx.doi.org/10.24014/jsms.v11i1.26998

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Jurnal JSMS

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