The limitations of observational rainfall data hamper the research process as well as development progress in a region. As an alternative solution, it is necessary to use optimized technology to replace observational rainfall data. CHRS Data Portal is one of the sites providing satellite rainfall data with five types of data. However, this research uses four types of data analyzed, namely PERSIANN, PERSIANN-CCS, PERSIANN-CDR, and PDIR-Now. These data are estimated from remotely sensed using Artificial Neural Network (ANN) which has a resolution of dan . The PERSIANN system is based on geostationary infrared imagery. This research discusses the effect of satellite rainfall data type on the mainstay discharge by quantifying the validity of the model using the NSE statistical parameter. For the analysis of regional rainfall using the Thiessen Polygon method, while for the analysis of the mainstay discharge using HEC-HMS software version 4.10 with the SCS Unit Hydrograph (UH-SCS) method. The results of this study show that all types of PERSIANN daily rainfall data can provide excellent simulations. The largest NSE value is generated from PERSIANN-CDR.