Application of Consumer Clustering Mining Data Mining in Household with Fuzzy Multi Criteria Decision Making (FMCDM)

  • Muhammad Anshari
  • I Putu Suryadharma
  • Nyoman Putra Sastra

Abstract

This study aims to classify consumers in the selection of houses using Fuzzy Multi Criteria Decision Making (FMCDM) method based on data mining. Alternative houses provided there are four of the minimalist houses, contemporary modern homes, classical houses, and traditional ethnic houses. To generate these choices, there are five criteria: price criteria, home/type criteria, interior criteria, exterior criteria, and home environmental criteria. The results of this study can help system users in determining the choice of home type based on the user's tastes of the criteria available and also can help the investors and contractors in building houses, villas, hotels, and housing of the criteria.

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Published
2017-09-23
How to Cite
ANSHARI, Muhammad; SURYADHARMA, I Putu; PUTRA SASTRA, Nyoman. Application of Consumer Clustering Mining Data Mining in Household with Fuzzy Multi Criteria Decision Making (FMCDM). International Journal of Engineering and Emerging Technology, [S.l.], v. 2, n. 1, p. 31-34, sep. 2017. ISSN 2579-5988. Available at: <https://ojs.unud.ac.id/index.php/ijeet/article/view/34583>. Date accessed: 02 nov. 2024.

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