PUTRA, BRILIAN MAHAYANA (2015) Grouping Website News on Similarity Link Using Page-rank Algorithm. Other thesis, Prodi Teknik Informatika Unika Soegijapranata.
|
Text (COVER)
11.02.0053 Brilian Mahayana Putra - COVER.pdf Download (7MB) | Preview |
|
![[img]](http://repository.unika.ac.id/style/images/fileicons/text.png) |
Text (BAB I)
11.02.0053 Brilian Mahayana Putra - BAB I.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (BAB II)
11.02.0053 Brilian Mahayana Putra - BAB II.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (BAB III)
11.02.0053 Brilian Mahayana Putra - BAB III.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (BAB IV)
11.02.0053 Brilian Mahayana Putra - BAB IV.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (BAB V)
11.02.0053 Brilian Mahayana Putra - BAB V.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (BAB VI)
11.02.0053 Brilian Mahayana Putra - BAB VI.pdf Restricted to Registered users only Download (7MB) |
|
|
Text (DAFTAR PUSTAKA)
11.02.0053 Brilian Mahayana Putra - DAFTAR PUSTAKA.pdf Download (7MB) | Preview |
|
|
Text (LAMPIRAN)
11.02.0053 Brilian Mahayana PutrA - LAMPIRAN.pdf Download (7MB) | Preview |
Abstract
Abstract — Grouping Website News on Similarity link using Page-rank Algorithm is classifying data based on similarity. With this grouping, user can easily know which website that contains a lot of news from a website news. Page-rank algorithm is an algorithm that are rarely used in data mining. Page-rank will find where the links come from. First, Page-rank algorithm will search incoming link each news article then the incoming link will stored in array. After that incoming link will be group by similarity. So, links that are already grouped will produce a recommendation. Final results of this grouping process is a recommendation for the reader. The reader can know any links that has a high degree of similarity links which linking in on the each article link.
| Item Type: | Thesis (Other) |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works |
| Divisions: | Faculty of Computer Science > Department of Informatics Engineering |
| Depositing User: | Mrs Christiana Sundari |
| Date Deposited: | 04 Nov 2015 08:41 |
| Last Modified: | 04 Nov 2015 08:41 |
| URI: | http://repository.unika.ac.id/id/eprint/5793 |
Actions (login required)
 |
View Item |
