Nyi Mas Dhyandra NurAnnisa,  2401989770

Data Mining in E-Service

Before going    into    further discussion, it would  be    better  if  we  know  better    what  data mining  and  e-service  are. Data mining  or  in  Indonesian  called    Data  Mining is a process that  is done  to  find  a  new  relationship  that  has  meanings,  patterns  and  habits by sorting through some of it.   data  stored  in storage  media  with  pattern  recognition  technologies such as  statistical  and  mathematical techniques, which  can be  inferred  into  an   interesting  pattern extraction  process  or Unique  from  large amounts  of  data.  Data mining  is a  combination  of  several  disciplines    that  bring together  techniques  from machine learning, pattern recognition,     statistics, databases,    and  visualization  for  handling  retrieval problems.   Large database    information.

The important  things  related to    data mining  are  as  follows:

1. Data mining is an automated process  of accessing existing data.
2. Data that will be processed  with  data mining  techniques is  data  with a very  large amount.
3. The purpose of data mining is  to get  patterns  that  might  provide useful  insights    to

Then E-Service  or Electronic Service System or E-Service is a leading online application that utilizes information and communication technology. Some examples of  e-services  are  e-learning, e-government, e-commerce, e-market, e-banking,  and so on.

Data mining is used  in  E-Services  to  provide insight and    improve  performance  in  many  ways. For  example  in  e-commerce services.  By  using  tools  and  techniques  in  extracting  data,  we  can find out the hidden  information  in a very large  amount of data, so  that  e-commerce  service  companies can  improve.  service  to  customers.

Processes in  data mining/webmining  include  data collection, pre-processing data, data storage, data mining  and  we  will  get the results of   information.

1. Data Collection

The first  thing  we have to  do  is certainly look for  the data  needed  to  find  hidden information.  In  e-commerce  data  needed  includes personal information    of customers including order history, complaints that have been submitted, search history, pages frequented, and other information that shows certain behavior of the customer. We  need to  do  customer profiling  to  find which  customers  have  the characteristics we  are  looking for,  so  not  all of our  customers  use the data.

2. Data Pre-Processing

Then we  have to sort out the data that  can be  used  (data cleansing) Data that  we do not  need  will be  deleted  and also get rid of  errors.

3. Data Storage

Once the  cleansing process is complete, the clean data  is  now  stored in a  database to make it easy  to  extract  and  use.

4. Data Mining

After ­cleaning  and  stored  in  a database,  we  choose  the technology  in  data mining  that  matches   the data  we  choose,  there are  many  data mining  technologies that  we can  use,  namely  associations. cluster,    classification,and sequential patterns.

5. Model Creation

Once we  do data mining,  there will  appear a variety  of different  models  and  only  a few  of   those  models  can be  used. Because  not  all  decision  makers  can  understand data mining  well,  themodel that  has been  obtained  must be  changed  back  in shape so that it is easily  understood  by users.

References

Kirshners, A., & Kornienko, Y. (2009). Time-Series Data Mining for E-Service Application Analysis. Scientific Journal of Riga Technical University Computer Sciences,94-100.

Mardi, Y. (n.d.). Data Mining: Classification Using C4.5 Algorithm. Journal of Informatics Edicacks. Research in computer science and informatics education,213-219.

Rastegari, H. (2008). DATA MINING AND E-COMMERCE: METHODS, APPLICATIONS, AND CHALLENGES. Journal of Information Technology,116-128.

Sunil, & Doja, M. N. (2017). WEB DATA MINING IN E-SERVICES – CONCEPTS AND APPLICATIONS. Indian Journal of Computer Science and Engineering.