01491nam a2200253 a 4500 vtls000067581 KUKTEM 20251114204529.0 121210t2012 my da f m 000 0 eng d THE0002013(Local) 201905131604 yusri 201301081242 huda 201212101541 huda UMP QA278 .H34 2012 rs Bc. Hafiz Kamal Leang Data clustering using maximum dependency of attributes and its application to cluster agricultural products / Hafiz Kamal Leang Kuantan, Pahang : UMP, 2012 xi, 105 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012 Bibliography : p. 86-91 This project is about understanding the method of Clustering Data using Rough set Theory. The technique used is Maximum Dependency of attributes. The way this technique work is by calculating the degree of each attribute and selecting the highest dependency based on the degree. The highest degree of attribute will be chosen as the best attribute to be used to cluster the data. A system will be built by using Visual Basic (VB) that will implement this technique to cluster large data faster and easier. Cluster analysis Data mining 0 0 0 1 10000 10000 2019-09-04 0 QA278 .H34 2012 rs Bc. 0000068745 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 6554 | QA278 .H34 2012 rs Bc. 0000068746 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 3637 3643 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992