{"id":4003,"date":"2021-12-19T23:49:22","date_gmt":"2021-12-19T16:49:22","guid":{"rendered":"http:\/\/bbs.binus.ac.id\/management\/?p=4003"},"modified":"2021-12-19T23:49:22","modified_gmt":"2021-12-19T16:49:22","slug":"data-mining-in-e-service","status":"publish","type":"post","link":"https:\/\/bbs.binus.ac.id\/management\/2021\/12\/data-mining-in-e-service\/","title":{"rendered":"Data Mining in E-Service"},"content":{"rendered":"

Nyi Mas Dhyandra NurAnnisa,\u00a0 2401989770<\/p>\n

Data Mining in E-Service<\/p>\n

Before going \u00a0\u00a0\u00a0into\u00a0\u00a0\u00a0 further discussion, it would\u00a0 be\u00a0\u00a0\u00a0 better\u00a0 if\u00a0 we\u00a0 know \u00a0better \u00a0\u00a0\u00a0what \u00a0data mining <\/em>\u00a0and \u00a0e-service<\/em> \u00a0are. Data mining <\/em>\u00a0or \u00a0in \u00a0Indonesian \u00a0called \u00a0\u00a0\u00a0Data \u00a0Mining is a process that \u00a0is done \u00a0to \u00a0find \u00a0a \u00a0new \u00a0relationship \u00a0that \u00a0has \u00a0meanings, \u00a0patterns \u00a0and \u00a0habits by sorting through some of it. \u00a0\u00a0data \u00a0stored \u00a0in storage \u00a0media\u00a0 with \u00a0pattern \u00a0recognition \u00a0technologies such as \u00a0statistical \u00a0and \u00a0mathematical techniques, which \u00a0can be \u00a0inferred \u00a0into \u00a0an \u00a0\u00a0interesting \u00a0pattern extraction \u00a0process\u00a0 or Unique\u00a0 from \u00a0large amounts \u00a0of \u00a0data. \u00a0Data mining <\/em>\u00a0is a \u00a0combination \u00a0of \u00a0several \u00a0disciplines \u00a0\u00a0\u00a0that \u00a0bring together \u00a0techniques \u00a0from machine learning, pattern recognition, <\/em>\u00a0\u00a0\u00a0\u00a0statistics, databases, \u00a0\u00a0<\/em>\u00a0and \u00a0visualization \u00a0for \u00a0handling \u00a0retrieval problems. \u00a0\u00a0Large database <\/em>\u00a0\u00a0\u00a0information.<\/p>\n

The important\u00a0 things\u00a0 related to\u00a0\u00a0 \u00a0data mining <\/em>\u00a0are\u00a0 as\u00a0 follows:<\/p>\n

    \n
  1. Data mining <\/em>is an automated process\u00a0 of accessing existing data.<\/li>\n
  2. Data that will be processed\u00a0 with \u00a0data mining <\/em>\u00a0techniques is\u00a0 data\u00a0 with a very\u00a0 large amount.<\/li>\n
  3. The purpose of data mining <\/em>is\u00a0 to get\u00a0 patterns\u00a0 that\u00a0 might\u00a0 provide useful \u00a0insights <\/em>\u00a0\u00a0\u00a0to<\/li>\n<\/ol>\n

    Then E-Service <\/em>\u00a0or Electronic Service System or E-Service is a leading online application that utilizes information and communication technology. Some examples of \u00a0e-services <\/em>\u00a0are \u00a0e-learning, e-government, e-commerce, e-market, e-banking, <\/em>\u00a0and so on.<\/p>\n

    Data mining is <\/em>used\u00a0 in\u00a0 E-Services\u00a0 to\u00a0 provide insight and <\/em>\u00a0\u00a0\u00a0improve\u00a0 performance\u00a0 in\u00a0 many\u00a0 ways. For \u00a0example \u00a0in \u00a0e-commerce<\/em> services.\u00a0 By \u00a0using \u00a0tools <\/em>\u00a0and \u00a0techniques \u00a0in \u00a0extracting \u00a0data, \u00a0we \u00a0can find out the hidden \u00a0information \u00a0in a very large \u00a0amount of data, so \u00a0that \u00a0e-commerce <\/em>\u00a0service \u00a0companies can \u00a0improve. \u00a0service \u00a0to \u00a0customers.<\/p>\n

    Processes in \u00a0data mining\/<\/em>webmining \u00a0include \u00a0data collection, pre-processing data, data storage, data mining <\/em>\u00a0and \u00a0we \u00a0will \u00a0get the results of \u00a0\u00a0information.<\/p>\n

      \n
    1. Data Collection<\/em><\/li>\n<\/ol>\n

      The first\u00a0 thing\u00a0 we have to\u00a0 do\u00a0 is certainly look for\u00a0 the data\u00a0 needed\u00a0 to\u00a0 find\u00a0 hidden information.\u00a0 In \u00a0e-commerce <\/em>\u00a0data\u00a0 needed\u00a0 includes personal information\u00a0\u00a0 \u00a0of customers <\/em>including order history, complaints that have been submitted, search history, pages frequented, and other information that shows certain behavior of the customer.<\/em> We \u00a0need to \u00a0do \u00a0customer profiling <\/em>\u00a0to \u00a0find which \u00a0customers <\/em>\u00a0have \u00a0the characteristics we \u00a0are\u00a0 looking for, \u00a0so \u00a0not \u00a0all of our \u00a0customers <\/em>\u00a0use the data.<\/p>\n

        \n
      1. Data Pre-Processing<\/em><\/li>\n<\/ol>\n

        Then we\u00a0 have to sort out the data that\u00a0 can be\u00a0 used\u00a0 (data cleansing) <\/em>Data that\u00a0 we do not\u00a0 need\u00a0 will be\u00a0 deleted\u00a0 and also get rid of\u00a0 errors.<\/p>\n

          \n
        1. Data Storage <\/em><\/li>\n<\/ol>\n

          Once the\u00a0 cleansing <\/em>process is complete, the clean data\u00a0 is\u00a0 now\u00a0 stored in a \u00a0database <\/em>to make it easy \u00a0to \u00a0extract \u00a0and \u00a0use.<\/p>\n

            \n
          1. Data Mining<\/em><\/li>\n<\/ol>\n

            After \u00adcleaning\u00a0 and\u00a0 stored\u00a0 in \u00a0a database, <\/em>\u00a0we\u00a0 choose \u00a0the technology \u00a0in \u00a0data mining <\/em>\u00a0that \u00a0matches \u00a0\u00a0the data \u00a0we \u00a0choose, \u00a0there are \u00a0many \u00a0data mining <\/em>\u00a0technologies that\u00a0 we can \u00a0use, \u00a0namely \u00a0associations. cluster, \u00a0\u00a0\u00a0classification,and sequential patterns.<\/em><\/p>\n

              \n
            1. Model Creation<\/li>\n<\/ol>\n

              Once we\u00a0 do data mining, <\/em>\u00a0there will\u00a0 appear a variety\u00a0 of different\u00a0 models\u00a0 and\u00a0 only\u00a0 a few\u00a0 of\u00a0\u00a0 those\u00a0 models\u00a0 can be\u00a0 used. Because\u00a0 not\u00a0 all\u00a0 decision\u00a0 makers\u00a0 can\u00a0 understand data mining <\/em>\u00a0well,\u00a0 themodel that\u00a0 has been\u00a0 obtained\u00a0 must be\u00a0 changed\u00a0 back\u00a0 in shape so that it is easily\u00a0 understood\u00a0 by users.<\/p>\n

              References<\/h6>\n

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

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

              Rastegari, H. (2008). DATA MINING AND E-COMMERCE: METHODS, APPLICATIONS, AND CHALLENGES. Journal of Information Technology,<\/em>116-128.<\/p>\n

              Sunil, & Doja, M. N. (2017). WEB DATA MINING IN E-SERVICES \u2013 CONCEPTS AND APPLICATIONS. Indian Journal of Computer Science and Engineering.<\/em><\/p>\n

               <\/p>\n

              <\/h1>\n

               <\/p>\n","protected":false},"excerpt":{"rendered":"

              Nyi Mas Dhyandra NurAnnisa,\u00a0 2401989770 Data Mining in E-Service Before going \u00a0\u00a0\u00a0into\u00a0\u00a0\u00a0 further discussion, it would\u00a0 be\u00a0\u00a0\u00a0 better\u00a0 if\u00a0 we\u00a0 know \u00a0better \u00a0\u00a0\u00a0what \u00a0data mining \u00a0and \u00a0e-service \u00a0are. Data mining \u00a0or \u00a0in \u00a0Indonesian \u00a0called \u00a0\u00a0\u00a0Data \u00a0Mining is a process that \u00a0is done \u00a0to \u00a0find \u00a0a \u00a0new \u00a0relationship \u00a0that \u00a0has \u00a0meanings, \u00a0patterns \u00a0and \u00a0habits by sorting […]<\/p>\n","protected":false},"author":9,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-4003","post","type-post","status-publish","format-standard","hentry","category-article"],"_links":{"self":[{"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/posts\/4003","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/comments?post=4003"}],"version-history":[{"count":1,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/posts\/4003\/revisions"}],"predecessor-version":[{"id":4004,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/posts\/4003\/revisions\/4004"}],"wp:attachment":[{"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/media?parent=4003"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/categories?post=4003"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bbs.binus.ac.id\/management\/wp-json\/wp\/v2\/tags?post=4003"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}