Previous researches outlined the advantages of AHP and ANP methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions, thus it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). This research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the Smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Five alternative products were chosen as the recommended smartphones. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product of F-ANP wa s greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-A`NP was more in line with the respondents’ preferences. As a result, the DSS-SmartPhoneRec application provided the best smartphone recommendations based on the user’s expectation. The system comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases .