## 4 Data Mining Analysis and Experimental Simulation
### Data Mining (Correlation Analysis)
#### 4.1.3 Non-Similarity Distribution Using Approximated Modified Jaccard Analysis (DAMJA)  
Before proceeding, we investigated the non-similarity percentages to see the data distribution of these non-similar values. In Tables 8 and 9, non-similar values are classified as high or low. If the difference between a student's GPAU and the corresponding score (GPAH, GAT, AT, WS, or QS) was greater than +10 points, it was classified as high, and if the difference between a student's GPAU and the corresponding score was smaller than \(-10\) points, it was classified as low; otherwise, it was classified as an approximated similarity (the approximated similarities already appear in Tables 6 and 7). The numbers of students are the same as those in Tables 4 and 5.  
Table 8 shows a classification of similar and non-similar AMJA results. For the major of medicine, first, the approximated similarity of GPAU and GPAH was 38.56%. No student had +10 GPAU in comparison with GPAH, and for 61.4% of students the GPAU was more than 10 points less than the GPAH. Second, for GPAU and GAT, the approximated similarity was 35.73%, where 29.19% was high and 35.1% was low. Third, for GPAU and AT the approximated similarity was 38.56%, where 18.95% was high and 44.5% was low. Fourth, for GPAU and QS the approximated similarity was 40.52%, where 11.98% was high and 47.49% was low. According to this investigation, a student who is classified as high performs better at university, which is a good indicator for major selection, even if they are not classified as an approximated similarity. This means that even if GPAU and QS have  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**College** & **GPAU—GPAH** & **GPAU—GAT** & **GPAU—AT** & **GPAU—QS** \\ \hline Medicine & 38.56 & 35.73 & 38.56 & 40.52 \\ Dentistry & 30.65 & 31.18 & 44.09 & 47.31 \\ Public Health and Tropical Medi & 12.56 & 21.09 & 25.44 & 28.34 \\ Nursing & 24.14 & 23.37 & 29.17 & 27.97 \\ Applied Medical Sciences & 22.36 & 22.07 & 27.27 & 29.18 \\ Pharmacy & 31.37 & 23.75 & 31.81 & 40.74 \\ Engineering & 12.37 & 27.17 & 28.75 & 28.96 \\ Computer Science and IT & 11.15 & 26.25 & 28.96 & 28.96 \\ Design and Architecture & 19.51 & 17.07 & 25.85 & 42.2 \\ Science & 6.17 & 24.99 & 29.7 & 28.44 \\ Business Administration & 19.98 & 20.02 & 18.99 & 27.29 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Illustrates AMJA between GPAU and GPAH, GAT, AT, and QS for scientific colleges.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**College** & **GPAU—GPAH** & **GPAU—GAT** & **GPAU—WS** \\ \hline Education & 50.67 & 3.31 & 9.77 \\ Sharia and Law & 25.72 & 2.71 & 8.46 \\ Arts and Humanities & 12.95 & 1.69 & 6.22 \\ \hline \hline \end{tabular}
\end{table}
Table 7: Illustrates AMJA between GPAU and GPAH, GAT, and WS for theoretical colleges.  
the highest approximated similarity, GPAU and AT are better since the total number of both the approximated similarity and high classification is the highest. This is also applicable for the majors of dentistry, public health, engineering, computer science and information technology, and business administration. In addition, the approximated similarity of GPAU and GAT is the best indicator for the majors of nursing, applied medical sciences, pharmacy, design and architecture, and science.  
On the other hand, for the majors of, Sharia and law, and arts and humanities, the approximated similarity of GPAU and GPAH is the highest, but by considering the advantages of those students who have high performances at university, the approximated similarity of GPAU and GAT becomes the best indicator for education majors and Sharia and law majors.  
In short, such variations demonstrate the weakness and inconsistency of current admission procedures and features.