# Binary Decision Support Using AHP: A Model for Alternative Analysis
## 5 Comparative Analysis  
A comparative analysis of the Binary AHP method with traditional AHP and other multi-criteria decision-making (MCDM) approaches revealed significant advantages in binary decision contexts. Conventional AHP requires the comparison of multiple alternatives, which creates a structural limitation when we apply it to purely binary (yes/no) decision scenarios. In contrast, Binary AHP addresses this limitation while retaining the core strengths of traditional AHP, such as clear hierarchical structuring and systematic pairwise comparison, by adapting its implementation to dichotomous choices.  
Unlike TOPSIS, which evaluates alternatives by measuring their distances from ideal solutions, Binary AHP directly incorporates two opposing alternatives within a single, coherent decision framework, eliminating the need to assess multiple intermediate options. When comparing Binary AHP with the Best-Worst Method (BWM), which requires consensus between experts on the best and worst criteria, Binary AHP offers greater flexibility to accommodate divergent expert opinions on critical aspects in complex decision environments, such as the public sector. Furthermore, while the FUCOM method streamlines the weighting process by minimizing the total deviation from consistency in the pairwise comparisons, Binary AHP provides the additional advantage of validating decision robustness through the transposed comparison matrix. This feature enables cross-verification and significantly enhances the confidence in the outcome.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Demands** & **ICT** & **Non-ICT** & **Result** \\ \hline Notebooks & 46\% & 16\% & ICT \\ Wireless keyboard acquisition & 4\% & 28\% & Non-ICT \\ Black wireless mouse mobile 1850 & 5\% & 19\% & Non-ICT \\ U7Z-00008 MFT Microsoft & 5\% & 19\% & Non-ICT \\ Procurement of wildcard digital certificate & 46\% & 25\% & ICT \\ Antivirus & 57\% & 12\% & ICT \\ Biometrics & 46\% & 25\% & ICT \\ CCTV camera & 47\% & 23\% & ICT \\ Digital certificate & 47\% & 13\% & ICT \\ Firefighting & 1\% & 12\% & Non-ICT \\ Computer and notebook & 47\% & 37\% & ICT \\ Scanner & 12\% & 31\% & Non-ICT \\ Public cloud & 59\% & 9\% & ICT \\ IT course/training & 5\% & 16\% & Non-ICT \\ Software for donation & 47\% & 15\% & ICT \\ Vehicle tracker & 52\% & 18\% & ICT \\ Computer and notebook for donation & 9\% & 22\% & Non-ICT \\ External hard drive and flash drive for & 9\% & 42\% & Non-ICT \\ donation & 1\% & 12\% & Non-ICT \\ Multifunction printer for donation & 1\% & 12\% & Non-ICT \\ Microsoft datacenter licenses & 56\% & 17\% & ICT \\ Switches & 56\% & 16\% & ICT \\ Artificial intelligence (research) & 47\% & 9\% & ICT \\ Peripherals (headphones, headset, keyboard, webcam, hard drive, etc.) & 8\% & 34\% & Non-ICT \\ Software development & 50\% & 7\% & ICT \\ Radio/radio communication & 57\% & 22\% & ICT \\ Printing service & 0\% & 21\% & Non-ICT \\ Tablet/notebook/ultrabook & 58\% & 21\% & ICT \\ Telephony & 6\% & 12\% & Non-ICT \\ Network server & 48\% & 19\% & ICT \\ \hline \end{tabular}
\end{table}
Table 18: _Cont._By allowing the evaluation of the decision from both perspectives (yes/no), Binary AHP ensures a more balanced and impartial analysis than traditional methods typically provide. By enabling a direct comparison of two mutually exclusive alternatives and incorporating mechanisms for verifying consistency and symmetry, Binary AHP offers a transparent and reproducible framework for binary classification problems.