Mentransformasi Pemilihan Sekolah: Integrasi Flask dan TOPSIS untuk Rekomendasi SMA yang berbasis Preferensi Individu
DOI:
https://doi.org/10.29408/edumatic.v9i3.32261Keywords:
adaptive weighting, decision support system, flask, high school selection, topsisAbstract
The selection of Senior High Schools (SMA) is often conducted subjectively without objective analysis, while previous studies on decision support systems (DSS) mostly used SAW or AHP methods with fixed weights, resulting in less adaptive recommendations. This study aims to develop and evaluate a web-based DSS integrating the TOPSIS method and Flask framework to provide SMA recommendations through customizable criteria weighting. The system was developed using the Waterfall model consisting of requirement analysis, design, implementation, and testing stages. Six main criteria were used: distance, location, academic achievement, non-academic achievement, accreditation, and extracurricular activities. The developed system successfully generates automated and responsive school recommendations based on user preferences. The black-box testing confirmed that all main functions worked properly, while the Spearman correlation test yielded a value of 0.9758, indicating very high accuracy and strong consistency between system results and manual calculations. These findings demonstrate that applying adaptive weighting within the TOPSIS method enriches the multi-criteria decision-making (MCDM) framework by introducing a personalized decision-making approach. Practically, the system assists users in making educational choices that are more objective, transparent, and aligned with individual needs.
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Copyright (c) 2025 Nur Khalidzah, Heliawati Hamrul, Farid Wajidi

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