Alternative Technique reducing complexity of Maximum Attribute Relation

Iwan Tri Riyadi Yanto, Imam Azhari


Clustering refers to the method grouping the large data into the smaller groups based on the similarity measure. Clustering techniques have been applied on numerical, categorical and mix data. One of the categorical data clustering technique based on the soft set theory is Maximum Attribute Relation (MAR). The MAR technique allows calculating all of pair multi soft set made. However, the computational complexity is still an issue of the technique. To overcome the drawback, the paper proposes the alternative algorithm to decrease the complexity so get the faster response time. In this paper, to get the similar results as MAR without calculating all pair of soft set is proved. The alternative algorithm is implemented in MATLAB Software, and then experimental is run on the 10 benchmark datasets. The results show that the alternative algorithm improves the computational complexity in term of response time up to 36.46%


Soft set, Multi Soft set, Attribute Relation

Full Text:



Article Metrics

Abstract view : 123 times
PDF - 118 times


  • There are currently no refbacks.

Copyright (c) 2015 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

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