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EVALUASI AKURASI MODEL HYBRID SIMPLE ADDITIVE WEIGHTING – WEIGHTED PRODUCT DENGAN PEMBOBOTAN ADAPTIF MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS UNTUK SELEKSI CALON PENGHUNI ASRAMA
This study examines the application of the Simple Additive Weighting (SAW) and Weighted Product (WP) methods, as well as their integration into a hybrid model with adaptive weighting based on the Analytic Hierarchy Process (AHP), for the selection of dormitory applicants. SAW has the advantage of computational simplicity, while WP is more sensitive to data variations. Both methods have limitations, making it necessary to combine them to obtain results that are more balanced, stable, and accurate. Adaptive weighting with AHP is employed to ensure that the criteria weights align with the dormitory administrators’ priorities and remain logically consistent. The eight criteria used include GPA, parents’ income and occupation, number of siblings, organizational activity, non-academic achievements, scholarship status, and semester. This study utilizes 120 alternative data, analyzed using SAW, WP, and the Hybrid SAW– WP method. The evaluation was carried out using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Spearman correlation. The results show that SAW – GT produces MAE = 10.67 and RMSE = 13.16. These error values are relatively high because the differences were calculated based on ranking (1–120), not the direct scores. Nevertheless, the Spearman correlation reached ρ = 0.928, indicating a very strong relationship. WP – GT obtained MAE = 5.96 and RMSE = 4.625, with a Spearman correlation of ρ = 0.985. This result is better than SAW, showing that WP is closer to GT in terms of ranking consistency. Meanwhile, Hybrid – GT achieved the best performance with MAE = 3.40 and RMSE = 4.57. The Spearman correlation reached ρ = 0.991, the highest among the three methods. This proves that the Hybrid method is the most consistent in replicating the GT ranking. In conclusion, the Hybrid SAW–WP with adaptive AHP weighting is not only consistent in producing rankings but also more stable compared to using a single method. This approach can be considered a more comprehensive solution for decision support systems, particularly in the context of dormitory applicant selection.
FAKULTAS SAINS DAN TEKNOLOGI, UIN SUNAN KALIJAGA YOGYAKARTA
EVALUASI AKURASI MODEL HYBRID SIMPLE ADDITIVE WEIGHTING – WEIGHTED PRODUCT DENGAN PEMBOBOTAN ADAPTIF MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS UNTUK SELEKSI CALON PENGHUNI ASRAMA (Text)
EVALUASI AKURASI MODEL HYBRID SIMPLE ADDITIVE WEIGHTING – WEIGHTED PRODUCT DENGAN PEMBOBOTAN ADAPTIF MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS UNTUK SELEKSI CALON PENGHUNI ASRAMA (Other)
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005.12 Software System Analysis and Design/Sistem Analisa dan Desain Perangkat Lunak