POLA AKSES PENGUNJUNG TOKO ONLINE MENGGUNAKAN WEIGHTED GRAPH WEB USAGE MINING (Studi Kasus Toko Koi Online)
The increase of online store growth is directly proportional with number of web usage data produced. Web Usage Mining can extract useful information based on web usage data. Some useful information for online store owner are frequently accessed webpages and items that attrack visitors. Nowadays, onl...
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Main Authors: | , |
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Format: | Theses and Dissertations NonPeerReviewed |
Published: |
[Yogyakarta] : Universitas Gadjah Mada
2013
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Subjects: | |
Online Access: | https://repository.ugm.ac.id/125754/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=65930 |
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Institution: | Universitas Gadjah Mada |
Summary: | The increase of online store growth is directly proportional with number of
web usage data produced. Web Usage Mining can extract useful information
based on web usage data. Some useful information for online store owner are
frequently accessed webpages and items that attrack visitors. Nowadays, online
store owner discover this information when visitors made a transaction. It
complicates online store owner to find out visitors interest in items. This research
aims to help online store owner discover visitor access patterns. Based on these
patterns, online store owner can discover frequently accessed webpages and items
that attrack visitors. This research uses Weighted Graph Web Usage Mining
method to extract online store visitor access pattern. This method covers web
usage data on client level use real time AJAX interface, pre-processing to
generate traversal database real time and Weighted Frequent Patterns Mining
method for pattern discovery. Result shows that Weighted Graph Web Usage
Mining can deliver information about frequently accessed webpages and items
that attrack visitors in certain periods based on visitor access patterns. This
method has average accuration of 65.5%. |
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