Research Paper
Year: 2020 | Month: April | Volume: 7 | Issue: 4 | Pages: 237-242
Implementation of Data Mining Using Clustering Methods for Analysis of Dangerous Disease Data
Rahayu Mayang Sari
Faculty of Science and Technology, Universitas Pembangunan Panca Budi, Medan, Indonesia
ABSTRACT
Method clustering with K-means algorithm used in data mining has the aim to explore information and knowledge from different perspectives but support each other method. Clustering with K-means algorithm gives information about the grouping of types of dangerous diseases, which suffer by patients. Analysis was performed using software Tanagra data mining1.4.38. The results of the data mining process are expected to provide its own benefits for the Islamic Hospital "Ibn Sina" Payakumbuh through new knowledge generated. Data mining is needed because there is a large amount of data that can be used to produce information and knowledge useful. The information and knowledge obtained can be used in many fields, ranging from business management, production control, health, etc.
Keywords: Data Mining, Clustering, K-Means
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