A Comparison Between FAHP-TOPSIS and FAHP-FTOPSIS Methods for Selecting the Best Products for Home-Based Sellers: A Performance Analysis

This study discusses common problems faced by home-based sellers in determining the right product ideas to sell. To overcome this problem, a method is needed that can help home-based sellers to choose the right product. Therefore, a decision support system using a multi-criteria decision-making technique with a hybrid approach was applied, which integrates the FAHP-TOPSIS and FAHP-FTOPSIS methods in the product selection process. The analysis results show that the FAHP-TOPSIS method is more effective in producing product rankings, with alternative A5948 ranking first with a score of 0.946. Meanwhile, the FAHP-FTOPSIS method also placed the same alternative in first place with a score of 0.679. The findings in the ranking analysis showed that the addition of fuzzy did not affect the rankings but did affect the score value of the alternatives. Sensitivity Analysis using Mean Absolute Deviation (MAD), Mean Square Error (MSE), and Spearman Correlation (SC) was conducted. FAHP-TOPSIS performed best at Weight 1 (MAD 89, MSE 18.486, SC 0.972) and excelled at Weight 3 (MAD 144, MSE 51.791, SC 0.997), though more volatile at other weights. Overall, at the base weight (Weight 1), TOPSIS shows the best ranking stability (low MAD/MSE, high SC), while with shifted weights (especially Weight 3), FTOPSIS better maintains ordering (SC ≈ 1) despite higher error at Weight 2. Practically, TOPSIS suits baseline scenarios; FTOPSIS is more robust under weight variations, with error variance control still necessary. These findings provide a practical guideline: use FAHP-FTOPSIS when preferences are uncertain, and use FAHP-TOPSIS when preferences are clear. The resulting rankings can be directly adopted by sellers to prioritize and select products with confidence.