Markov Chain Analysis in Predicting Consumer Price Index for the Food, Beverage and Tobacco Sector in Jambi City
Keywords:
Consumer Price Index, Markov Chain, ProbabilityAbstract
The Consumer Price Index (CPI) is an economic indicator that can provide information regarding developments in prices of goods/services. CPI is one of the factors that can measure inflation. According to the information provided, inflation pressure is influenced by the food, beverage and tobacco sectors and is one of the mainstays in providing a major contribution to economic growth. Every month the CPI can increase or decrease so data from previous times is used to see predictions for the present so time series data is used. Prediction of CPI time series data can use one of the mathematical techniques, namely Markov chain analysis. Markov chain is a method that studies the properties of a variable in the present in an effort to estimate the properties of the same variable in the future, therefore Markov chain analysis is suitable for use in predicting CPI. In this research, it was applied to CPI data for January 2018 to June 2022. After conducting the analysis, it was concluded that in the following months the opportunity for CPI in categories above the basic price was greater than the opportunity above the basic price. So it is hoped that the results of this analysis can help the government stabilize the CPI in the Food, Miniman and Tobacco sectors
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