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| Analisis Keputusan Multi-Kriteria Berbasis Data× | Teknik untuk Urutan Preferensi berdasarkan Kesamaan dengan Solusi Ideal× | |
|---|---|---|
| Bidang | Pengambilan Keputusan | Pengambilan Keputusan |
| Keluarga | MCDM | MCDM |
| Tahun asal≠ | 2015 | 1981 |
| Pencetus≠ | Multiple authors | Hwang, C. L., Yoon, K. |
| Tipe≠ | Learning-based criteria weighting and aggregation | Distance-based (compromise) |
| Sumber perintis≠ | Греченко, Д. В. (2019). Data-driven decision making: Integrating machine learning with multi-criteria approaches. Computational Statistics & Data Analysis, 132, 127-143. link ↗ | Hwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications — A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗ |
| Alias≠ | Data-Driven MCDA | — |
| Terkait≠ | 5 | 8 |
| Ringkasan≠ | Data-Driven MCDA is a hybrid framework that integrates machine learning and statistical learning into traditional multi-criteria decision analysis. Instead of eliciting weights from expert judgment, it learns criteria importance from historical decision data, enabling more scalable and empirically grounded decision support. | TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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