Counting residential houses is one of the problems faced when determining population density level in Indonesia, therefore it’s required to find a method that’s able to solve said problem. Deep learning method is capable of creating a prediction model for detecting the number of buildings from an image. The deep learning prediction model is created with MobileNetv2 application. The prediction model is trained by using a dataset from Kaggle. The prediction model is tested using satellite photos taken from Way Kandis-Sukarame, Bandar Lampung. The result is a deep learning prediction model with accuracy of 91.30% for SenseFly and 10.34% for Way Kandis dataset. The research can be further improved by using a better training and testing dataset
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