01867nam a2200253 a 4500 vtls000067645 KUKTEM 20251114204524.0 121211t2012 my da f m 000 0 eng d THE0002016(Local) 201905131605 yusri 201301081435 huda 201212111651 huda UMP QA278 .R53 2012 rs Bc. Mohd Ridzuan Baharin Data clustering using min-min roughness and its application to cluster patients suspected diabetics / Mohd Ridzuan Baharin Kuantan, Pahang : UMP, 2012 102 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012 Includes bibliographical references In the context of information technology nowadays, there are many data exists. All of this data are scrambled over inside the computer and with the presence of internet, even more data exist. The problem with this is, when we want the needed data only, there are too many to look for and they are all scrambled over the internet databases. Therefore, there are techniques that are proposed that will provide a way to automatically mine the data and obtain only meaningful data from the huge data over the internet. The area discussed in this research is Knowledge Discovery in Databases (KDD) and the technique used is Minimum-Minimum Roughness (MMR). The dataset used will be the dataset of diabetic patients. By using this MMR technique, I intended to cluster the diabetic dataset n which each cluster will contain the data most related to each other. Cluster analysis Cluster analysis Data processing 0 0 0 1 10000 10000 2019-09-04 0 QA278 .R53 2012 rs Bc. 0000068729 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 6546 | QA278 .R53 2012 rs Bc. 0000068730 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 3493 3499 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992