OPTIMASI FUZZY INFERENCE SYSTEM SUGENO DENGAN ALGORITMA HILL CLIMBING UNTUK PENENTUAN HARGA JUAL RUMAH

Arinda Hapsari Achnas, Imam Cholissodin, Wayan Firdaus Mahmudy

Abstract


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.


Full Text:

PDF

References


CHIRA, C., HORVATH, D., & DUMITRESCU. 2011. Hill Climbing Search and Diversification Within An Evolutionary Approach to Protein Structure Prediction. US: Natural Center for Biotechnology Information. National Library of Medicine.

KUSAN, H., AYTEKIN, O., & OZDEMIR, I. 2010. The Use Of Fuzzy Logic In Predicting House Selling Price. Turkey: Departement of Civil Engineering , Eskisehir Osmangazi University.

LANGLEY, P., GENNARI, J., & IBA, W. 2008. Hill-Climbing Theories Of Learning. California: Irvine Computational Intelligence Project. Departement of Information & Computer Science. University of California. Irvine,.

MAHMUDY, W. F., MARIAN, R. M. & LUONG, L. H. S. 2013. Real coded genetic algorithms for solving flexible job-shop scheduling problem – Part II: optimization. Advanced Materials Research, no. 701, pp. 364-369.

MAHMUDY, W.F. 2014. Optimasi part type selection and machine loading problems pada FMS menggunakan metode particle swarm optimization (Optimization of part type selection and machine loading problems in FMS using particle swarm optimization', Konferensi Nasional Sistem Informasi (KNSI) STMIK Dipanegara, Makassar, 27 Februari - 1 Maret, pp. 1718-1723.

PUTRA, I. K., AISJAH, A. S., & ARIFIN, S. 2014. Perancangan Sistem Prediksi Suhu Permukaan Laut dengan Adaptive Neuro Fuzzy Inference Sytem (ANFIS) pada Maritime Weather Station di Perairan Dangkal Jawa Timur. Surabaya: Jurusan Teknik Fisika. Fakultas Teknologi Industri Institut Teknologi Sepuluh Nopember.

SANTOSO, U. 2014. Hukum Perumahan. Jakarta: Kencana Prenadamedia.




DOI: http://dx.doi.org/10.21776/ub.jeest.2015.002.01.5

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.