<![CDATA[Accurate rainfall data in terms of time and space is greatly needed across many sectors. This study evaluates rainfall data using information from two satellites, namely the Global Precipitation Measurement (GPM) and Global Satellite Measurement of Precipitation (GSMaP), employing statistical indicators such as correlation coefficient, MAE, RMSE, Mann-Whitney test, RAPS, and Weibull distribution. The comparative analysis between surface rainfall data and data from the GPM and GSMaP satellites shows a satisfactory level of agreement, proving that satellite-based rainfall measurement techniques are reliable. After correction of the rainfall data at the Air Molek Station in the Indragiri River Basin, the results indicate a perfect correlation of 1, meaning that the station's data matches very well with the satellite data and falls into the very good category. The application of the stepwise regression method to develop correction equations successfully improved the accuracy of rainfall predictions from the GPM and GSMaP satellites, as evidenced by the increase in correlation coefficient and significant decrease in error values. These findings confirm that the developed correction equations are effective in improving the agreement between satellite data and ground data, thereby making satellite data more reliable for monitoring rainfall.]]>
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