The development of smartphones nowadays is incredibly rapid, from the early generations to the current ones. This development has led to an increasing number of smartphone vendors offering products with many modern features and options. The diversity of brands, specifications, and prices offered usually cannot be adjusted to the needs of users. On the other hand, most users do not understand the meaning of smartphone specifications and just choose based on the appearance without paying attention to the functionality of the smartphone. From the above problems, a system is needed as a tool to make decisions. The K-Nearest Neighbor algorithm can be used to support decision making. The algorithm runs by determining the closest distance and variable data options, so that users can choose according to the desired functionality. Researchers designed a "Decision Support System for Smartphone Selection Using the K-Nearest Neighbor (KNN) Method Based on WEB" to overcome the above problems. The results obtained from Black Box testing are quite satisfying in terms of system functionality and algorithms, but there are problems in the Processor Selection section. In the processor selection section, the parameters created are influenced and cannot cover all data from the processor. In the expert system testing scheme, there were 14 correct classification results out of 8 and the total accuracy obtained was 57%. The smartphone decision support system using the K-Nearest Neighbor algorithm can be implemented well.