<![CDATA[The problem of poverty is one of the important problems that must be addressed by the government. In connection with this, a computer program is designed that can analyze the poverty level of the Indonesian population using the Markov Chain method. In designing this program, secondary data from BPS is used on the Number of Poor Population, Percentage of Poor Population (%), Poverty Line (Rp), Poverty Depth Index (P1), Poverty Severity Index (P2) from 2019-2022 at the provincial level in Indonesia. . The data analysis technique used in forecasting the poverty rate in the Indonesian Territory is the Markov Chain method. All data from variables are grouped into 7 stages. The transition matrix shows the magnitude of the value transfer from one stage to another, arranged based on the displacement from one year to the next. The forecast results of all poverty variables indicate that there is a tendency for a decrease in the level of poverty in the territory of Indonesia and the program design uses Java SE.]]>
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