Weather is one of the most unpredictable things in Indonesia. One of the factors is because Indonesia is an archipelago flanked by two vast oceans, the Indian Ocean and the Pacific Ocean. In addition, Indonesia, which is known as an “equatorial country”, creates uncertainty and changes in weather movements very quickly. So, until now the Meteorology, Climatology and Geophysics Agency (BMKG) still has difficulty predicting the weather accurately. The Deep Learning approach is used to analyze and process weather data in this study. Observation data as many as 7 bands are used to generate 13 rain parameters that will be used as rain predictors. The deep learning algorithm used is the Long-Short Term Memory (LSTM) algorithm which is often used for processing data in the form of time series. This study provides a recommendation analysis of rain detection parameter combinations for heavy rain prediction and compares 1-hour and 2-hour heavy rain prediction models. This research uses a dataset of 8738 data from Septe