In recent years, Instagram has become one of top 15 online social networks. However, popularity of Instagram also causes advertisement and spam posts flooding. Therefore, it is necessary to build a spam detection model to decrease number of spam posts in Instagram. We present a scheme applying feature-based method and supervised learning technique to detect spam posts from Instagram. We use K-fold cross validation to find best pair of supervised learning model and parameters of the model and accuracy of our best model is 96.27%.