TY - GEN
T1 - Hybrid School Selection System Using R-Tree Spatial Index Algorithm and SAW Method
AU - Sunaryono, Dwi
AU - Purwananto, Yudhi
AU - Sabilla, Irzal Ahmad
AU - Wijaya, William Handi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In 2022 East Java new students admission, the verifier school and recommended schools determination system can still be improved because some students still get a school that is either far from their residence or has a long verification queue. Therefore, the purpose of the proposed research is to design a hybrid school selection system using R-Tree spatial index algorithm and Simple Additive Weighting (SAW) method in the case study of 2022 East Java new students admission. This research is also proposed to fill the gap in performance comparison between system that use MCDM method with and without spatial index. The performance of the spatial index system, non spatial index system, and the old system used in 2022 East Java new students admission will be compared using random sample from students dataset in 2022 East Java new students admission. After performance evaluation, it can be concluded that the spatial index system has an accuracy of 99.96% when compared to the system without spatial index. Additionally, in terms of time, the spatial index system also shows a performance improvement of 57.56% compared to the system without spatial index. Furthermore, the system employing spatial indexing and the Simple Additive Weighting (SAW) method also surpasses the legacy system by 1.28% in terms of decision quality (accuracy).
AB - In 2022 East Java new students admission, the verifier school and recommended schools determination system can still be improved because some students still get a school that is either far from their residence or has a long verification queue. Therefore, the purpose of the proposed research is to design a hybrid school selection system using R-Tree spatial index algorithm and Simple Additive Weighting (SAW) method in the case study of 2022 East Java new students admission. This research is also proposed to fill the gap in performance comparison between system that use MCDM method with and without spatial index. The performance of the spatial index system, non spatial index system, and the old system used in 2022 East Java new students admission will be compared using random sample from students dataset in 2022 East Java new students admission. After performance evaluation, it can be concluded that the spatial index system has an accuracy of 99.96% when compared to the system without spatial index. Additionally, in terms of time, the spatial index system also shows a performance improvement of 57.56% compared to the system without spatial index. Furthermore, the system employing spatial indexing and the Simple Additive Weighting (SAW) method also surpasses the legacy system by 1.28% in terms of decision quality (accuracy).
KW - 2022 East Java new students admission
KW - multi-criteria decision method (MCDM)
KW - r-tree algorithm
KW - simple additive weighting (SAW)
KW - spatial index
UR - http://www.scopus.com/inward/record.url?scp=85190069683&partnerID=8YFLogxK
U2 - 10.1109/ICONNIC59854.2023.10467541
DO - 10.1109/ICONNIC59854.2023.10467541
M3 - Conference contribution
AN - SCOPUS:85190069683
T3 - 2023 1st International Conference on Advanced Engineering and Technologies, ICONNIC 2023 - Proceeding
SP - 362
EP - 367
BT - 2023 1st International Conference on Advanced Engineering and Technologies, ICONNIC 2023 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st International Conference on Advanced Engineering and Technologies, ICONNIC 2023
Y2 - 14 October 2023
ER -