Sensitivity Analysis of a Simple Additive Weighting-Based Decision Support System for Strategic E-Learning Evaluation
Analisis Sensitivitas Sistem Pendukung Keputusan Berbasis Simple Additive Weighting untuk Evaluasi Strategis E-Learning
DOI:
https://doi.org/10.33050/sensi.v12i2.4529Keywords:
SPK, SAW, Sensitivity Analysis, E-Learning, , Data-Driven Decision.Abstract
The implementation of e-learning often faces obstacles in the objectivity of student performance evaluations which have an impact on the inaccuracy of managerial decision-making. This study aims to design a Decision Support System (SPK) using the Simple Additive Weighting (SAW) method which is integrated with sensitivity analysis. Four main criteria were used: forum activity (25%), task accuracy (30%), evaluation value (30%), and duration of access (15%). The simulation results showed that the system succeeded in classifying students into three categories
of adaptivity, with Citra (A3) being the highest ranked (score of 0.98). Crucial findings from the sensitivity analysis showed that although the weight of the interaction was increased by 40%, the ranking order remained robust, but the score in the passive student group decreased significantly to 0.46 (below the critical threshold of 0.50). This proves that the model not only functions as a ranking tool, but also as a precise early warning system for university management to carry out data-driven preventive interventions.
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