Application of Markov Chain to Prediction Poverty in Banten Province

Besse Arnawisuda Ningsi; Dinda Novianda Putri

doi:10.31764/jtam.v7i1.10057

Application of Markov Chain to Prediction Poverty in Banten Province

Besse Arnawisuda Ningsi, Dinda Novianda Putri

Abstract

The number of poor people in Banten Province is in the third lowest position in Java Island under the Special Region Province of the Capital Jakarta and Yogyakarta Special Region Province in 2018-2020 until finally it is in the second lowest position in 2021. However, this does not mean that the problem of poverty is no longer a top priority. This study aims to apply the Markov chain in predicting poverty in Banten Province. According to Marli et al. (2018) The Markov chain is a method that studies the properties of a variable in the present based on its past properties to estimate the properties of these variables in the future. In this research, the type of research used is applied research and used secondary data sourced from the Central Statistics Agency (BPS) Banten Province. The poverty prediction results for Pandeglang Regency in 2022, 2023 and 2024-2025 will increase by 2%, 0.46%, and 0.02%, respectively. Lebak Regency in 2022 will increase by 2%, in 2023 and in 2024-2025 it will decrease by 0.66% and 0.01%, respectively. Tangerang Regency in 2022 will decrease by 4%, in 2023 it will increase by 0.99%, and will fall back in 2024-2025 by 0.01%. Serang Regency in 2022 will increase by 1%, in 2023-2025 it will decrease by 0.83%. Tangerang City in 2022 remains, in 2023 and 2024-2025 it will increase by 0.53% and 0.01%, respectively. The city of Cilegon in 2022 remains, in 2023 it will increase by 0.18% and 2024-2025 will decrease by 0.01%. Serang City in 2022 remains, in 2023-2025 it will decrease by 0.71%. South Tangerang City in 2022 will decrease by 1%, in 2023-2025 it will increase by 0.04%. The steady state probability of Pandeglang Regency is 17.48%, Lebak Regency is 17.33%, Tangerang Regency is 27.98%, Serang Regency is 10.17%, Tangerang City is 15.54%, Cilegon City is 2.17%, Serang City is 5.29% and South Tangerang City is 4.04%..

Keywords

Poverty; Prediction; Probability; Markov chain.

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DOI: https://doi.org/10.31764/jtam.v7i1.10057