scholarly journals Analysis of employee's satisfaction factor in working environment using data mining algorithm

2014 ◽  
Vol 16 (4) ◽  
pp. 275-284
Author(s):  
Dong Ryeol Lee ◽  
Tae Ho Kim ◽  
HongChul Lee
Keyword(s):  
Data Mining ◽  
Working Environment ◽  
Data Mining Algorithm ◽  
Mining Algorithm ◽  
Using Data

Noninvasive prediction of HCV-4 SVR by 2D US: a randomized study using data mining algorithm

2016 ◽  
Vol 14 (1) ◽  
pp. 14
Author(s):  
Hamdy Mahfouz ◽  
AbdElrazek M. Ali Abd Elrazek ◽  
Khaled Abdelazeem ◽  
MohammadAbd Elfattah ◽  
Mahmoud Foad ◽  
...  
Keyword(s):  
Data Mining ◽  
Randomized Study ◽  
Data Mining Algorithm ◽  
Mining Algorithm ◽  
Using Data

scholarly journals Analysis of sales levels of pharmaceutical products by using data mining algorithm C45

2021 ◽  
Vol 22 (1) ◽  
pp. 476
Author(s):  
Rini Sovia ◽  
Abulwafa Muhammad ◽  
Syafri Arlis ◽  
Guslendra Guslendra ◽  
Sarjon Defit
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Data Processing ◽  
Medicinal Product ◽  
Pharmaceutical Products ◽  
Data Mining Algorithm ◽  
Sales Data ◽  
Great Demand ◽  
Mining Algorithm ◽  
Using Data

<p>This research was conducted to analyze the level of sales of pharmaceutical products at a Pharmacy. This is done to find out the types of products that have high and low sales levels. This study uses the C45 Data Mining Algorithm concept that will produce a conclusion on the prediction of sales of pharmaceutical products through data processing obtained from sales transactions at pharmacies. This C45 algorithm will form a decision tree that provides users with knowledge about products that are in great demand by consumers based on sales data and predetermined variables. The final result of the C45 algorithm produces a number of rules that can identify the inheritance of a type of medicinal product. C45 algorithm is able to produce 20 types of categories that will be labeled goals based on the number of pharmaceutical products, since it can be concluded that C45 successfully defines 55% of the existing objective categories.</p>

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