OPTIMASI FUZZY INFERENCE SYSTEM SUGENO DENGAN ALGORITMA HILL CLIMBING UNTUK PENENTUAN HARGA JUAL RUMAH
| Main Authors: | Achnas, Arinda Hapsari, Cholissodin, Imam, Mahmudy, Wayan Firdaus |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya
, 2015
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| Online Access: |
https://jeest.ub.ac.id/index.php/jeest/article/view/26 https://jeest.ub.ac.id/index.php/jeest/article/view/26/55 https://jeest.ub.ac.id/index.php/jeest/article/downloadSuppFile/26/40 |
Daftar Isi:
- A house selling price can be determined by two methods, financially and technically. Hovewer, the selling price that determined by the methods are often different. It makes the manager having a problem when determining the house final selling price accurately. This paper proposes Sugeno Fuzzy Inference System (FIS) to calculate an accurate price. To get better result, Hill Climbing Algorithms is used to optimize the membership function of Sugeno FIS. A series of computational experimens prove that the approach is effective. Hill Climbing Algorithms can improve the accuracy of results.