## 4 Numerical Results
### Indicator Weighting  
Table 3 presents the normalized decision matrix, which is constructed based on the ten alternatives' indicators and Equation (7). The under-risk utility matrix is derived in Table 4 by utilizing Equation (8). As indicated in Table 5, the regret utility matrix is then constructed using Equation (9). According to Equation (10), Table 6 illustrates the final utility matrix. The standard deviation is determined for all eight indicators using Equation (11). Then, based on Equations (12) and (13), the Euclidean distance matrix between the alternatives' total utilities is estimated. Table A1 is an example of an indicator C1, Euclidean Distance matrix. In addition, recalculating using the remaining indications based on Equation (14), the mean of the additional matrix is calculated as shown in Table A2. Next, the distance variance of indicators is calculated as shown in Table A3. The computation is then repeated with the remaining indicators. The distance covariance between the C1 and C2 indicators is shown in Table A4. The computation is then repeated with the remaining indicators. The \(dCOR\) matrix is shown in Table A5. The weight of indicators is calculated according \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Country** & **Code** & **C1** & **C2** & **C3** & **C4** & **C5** & **C6** & **C7** & **C8** \\  & **(0–1 Scale)** & **(0–1 Scale)** & **(\%)** & **(0–1 Scale)** & **(0–1 Scale)** & **(\%)** & **(0–1 Scale)** & **(\%)** & **(No. of TLS/SSL)** & **(People)** \\ \hline Brunei & BN & 0.4773 & 0.5871 & 91.3462 & 0.8372 & 0.7567 & 81.2944 & 14,703 & 517,740 \\ Cambodia & KH & 0.2841 & 0.4181 & 36.0577 & 0.5605 & 0.538 & 69.137 & 651,189 & 298,238,245 \\ Indonesia & ID & 0.7159 & 0.7644 & 65.3846 & 0.6397 & 0.7438 & 69.3884 & 4521 & 17,883,678 \\ Lao PDR & LA & 0.2614 & 0.3005 & 30.2885 & 0.282 & 0.5468 & 56.5393 & 1054 & 8,009,566 \\ Malaysia & MY & 0.6818 & 0.763 & 81.25 & 0.7945 & 0.7645 & 56.5393 & 1016 & 58,328,992 \\ Myanmar & MM & 0.3068 & 0.3073 & 8.65385 & 0.6082 & 0.5829 & 80.8361 & 308,704 & 37,242,523 \\ Philippines & PH & 0.4886 & 0.6303 & 57.6923 & 0.5638 & 0.7629 & 62.3952 & 13,303 & 122,056,425 \\ Singapore & SG & 0.9773 & 0.962 & 100 & 0.8758 & 0.9021 & 93.4973 & 796,767 & 6,268,858 \\ Thailand & TH & 0.7841 & 0.7763 & 60.5769 & 0.7338 & 0.7879 & 90.173 & 243,223 & 80,502,792 \\ Vietnam & VN & 0.5341 & 0.6484 & 62.0192 & 0.6973 & 0.6903 & 80.7708 & 438,126 & 106,757,032 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Decision matrix. to Equation (17) and is shown in Figure 2. Consequently, secure internet servers (C7), UHC service coverage index (C6), and Population (C8) are the three most significant indicators, with respective values of 0.195, 0.173, and 0.151. The weight of the Government Effectiveness (C3) and Human capital Index factors (C5) with the least significance is 0.093. Meanwhile, there is no substantial variation in weight among the other indicators. Consequently, the quality of an economy's infrastructure, especially its electricity and connectivity, is a crucial factor for both local and international investors when making investment choices. Information and communication technologies are widely acknowledged as crucial instruments for advancement, assisting in global cooperation and promoting public sector performance, productivity, and accountability. Moreover, the responsiveness of a nation's health system to necessary services is crucial and needed. This indicates the quality of life of the people and the government's concern for their citizen's security. In addition, population size is compared to the necessity for a universal healthcare system;