Sentinel-1A imagery can be used for various purposes, such as surveys and agricultural land use mapping. For example, Sentinel-1A image can be used to carry out land processing and validate crop yields from horticultural crops such as garlic. However, the acquisition and download of Sentinel images are currently done manually with several stages, so it still needs to be more effective and efficient. Therefore, an alternative way to support the acquisition of sentinel data is necessary by optimizing the process of automating the download of Sentinel data. This study aims to build a front-end module to automate the downloading of web-based Sentinel image data using the Django Framework. The prototyping method is used to develop a front-end module for Sentinel image download automation. This method was chosen based on its advantages in getting feedback from each user from every iteration carried out so that improvements can be made quickly according to user needs. The result of this research is an automated system for downloading Sentinel-1A images that can download Sentinel image data via maps or by validating geoJson data entered by the user. The development of this system is carried out in two iterations. All functions in the developed module were successfully performed in black box testing without showing any errors.
                        
                        
                        
                        
                            
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