Enumeration of Reading Ability of Tamil Newspaper and Classification of Writing Style Using Data Mining

Author(s):  
R. Lakshmi Priya ◽  
G. Manimannan
Author(s):  
Roma Sahani ◽  
Shatabdinalini ◽  
Chinmayee Rout ◽  
J. Chandrakanta Badajena ◽  
Ajay Kumar Jena ◽  
...  

Author(s):  
Pinku Deb Nath ◽  
Sowvik Kanti Das ◽  
Fabiha Nazmi Islam ◽  
Kifayat Tahmid ◽  
Raufir Ahmed Shanto ◽  
...  

2018 ◽  
Vol 150 ◽  
pp. 06003 ◽  
Author(s):  
Saima Anwar Lashari ◽  
Rosziati Ibrahim ◽  
Norhalina Senan ◽  
N. S. A. M. Taujuddin

This paper investigates the existing practices and prospects of medical data classification based on data mining techniques. It highlights major advanced classification approaches used to enhance classification accuracy. Past research has provided literature on medical data classification using data mining techniques. From extensive literature analysis, it is found that data mining techniques are very effective for the task of classification. This paper analysed comparatively the current advancement in the classification of medical data. The findings of the study showed that the existing classification of medical data can be improved further. Nonetheless, there should be more research to ascertain and lessen the ambiguities for classification to gain better precision.


Author(s):  
Jeprianto Sinaga ◽  
Bosker Sinaga

Unsecured loans are the community's choice for lending to banks that provide Reviews These services. PT. RB Diori Ganda is a regional private banking company that serves savings and loans and loans without collateral for the community. Submission of unsecured loans must go through an assessor team to process the analysis of the attributes that Affect the customer's classification so that credit can be approved, the which is then submitted to the commissioner for credit approval. But what if Reviews those who apply for credit on the same day in large amounts, of course this will the make the process of credit analysis and approval will take a long time. If it is seen from the many needs of the community to apply for loans without collateral, a classification application is needed, in order to Facilitate the work of the assessor team in the process of analyzing the attributes that Affect customer classification. To find out the classification of customers who apply for unsecured loans for using data mining with the K-Nearest Neighbor algorithm. The result of this research is the classification of problematic or non-performing customers for credit applications without collateral.


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