Learning Klasifikasi Bayesian Network Menggunakan Algoritma Conditional Independence Test
| Main Author: | Yustiar Fradhany |
|---|---|
| Format: | Bachelors |
| Terbitan: |
Universitas Telkom
, 2008
|
| Subjects: | |
| Online Access: |
https://openlibrary.telkomuniversity.ac.id/pustaka/94486/learning-klasifikasi-bayesian-network-menggunakan-algoritma-conditional-independence-test.html |
| ctrlnum |
113040011 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><title>Learning Klasifikasi Bayesian Network Menggunakan Algoritma Conditional Independence Test</title><creator>Yustiar Fradhany</creator><subject>Rekayasa Perangkat Lunak</subject><description>ABSTRAKSI: Data mining merupakan serangkaian proses untuk menggali nilai tambah dari suatu kumpulan data berupa pengetahuan yang selama ini tidak diketahui. Ada beberapa task dalam data mining, salah satunya adalah klasifikasi. Dalam Tugas Akhir ini akan digunakan metode klasifikasi Bayesian Network Classifier.<br> Bayesian Network (BN) Classifier menggambarkan suatu distribusi joint probability dari sebuah set atribut. BN merupakan graf asiklik berarah yang node-nodenya merepresentasikan variable pada data set sedangkan busur-busurnya (arc) merepresentasikan relasi ketergantungan diantara variable tersebut.<br> Tugas Akhir ini bertujuan untuk menganalisis performansi waktu klasifikasi dan akurasi dari Bayesian Network (BN) Classifier pada Naïve Bayes dan TAN Classifier yang pemodelannya dibangun menggunakan algoritma conditional independence test.<br>Kata Kunci : Kata Kunci: Bayesian Network Classifier, klasifikasi, data mining. Conditional independence test, Naïve Bayes, TAN.<br>ABSTRACT: Data mining is a process to find out the potential of information implicitly from database which unknown identifier before. One of many tasks in data mining that would be the subject of this final project is classification, especially Bayesian Networks (BN) Classifier.<br> Bayesian Networks (BN) is a directed acyclic graph whose nodes represent variables and arcs represent statistical dependence relations among the variables and local probability distributions for each variable given values of its parents.<br> This final project analyzes the performance and accuracy of Naïve Bayes classifier and Tree Augmented Naïve Bayes classifier as classification technique of BN which build using conditional independence test based algorithms.<br>Keyword: Keywords: Bayesian Network Classifier, classification, data mining. Conditional independence test, Naïve Bayes, TAN.</description><publisher>Universitas Telkom</publisher><date>2008-01-01</date><type>Thesis:Bachelors</type><identifier>https://openlibrary.telkomuniversity.ac.id/pustaka/94486/learning-klasifikasi-bayesian-network-menggunakan-algoritma-conditional-independence-test.html</identifier><language>Indonesia</language><recordID>113040011</recordID></dc>
|
| format |
Thesis:Bachelors Thesis |
| author |
Yustiar Fradhany |
| title |
Learning Klasifikasi Bayesian Network Menggunakan Algoritma Conditional Independence Test |
| publisher |
Universitas Telkom |
| publishDate |
2008 |
| topic |
Rekayasa Perangkat Lunak |
| url |
https://openlibrary.telkomuniversity.ac.id/pustaka/94486/learning-klasifikasi-bayesian-network-menggunakan-algoritma-conditional-independence-test.html |
| contents |
ABSTRAKSI: Data mining merupakan serangkaian proses untuk menggali nilai tambah dari suatu kumpulan data berupa pengetahuan yang selama ini tidak diketahui. Ada beberapa task dalam data mining, salah satunya adalah klasifikasi. Dalam Tugas Akhir ini akan digunakan metode klasifikasi Bayesian Network Classifier.<br> Bayesian Network (BN) Classifier menggambarkan suatu distribusi joint probability dari sebuah set atribut. BN merupakan graf asiklik berarah yang node-nodenya merepresentasikan variable pada data set sedangkan busur-busurnya (arc) merepresentasikan relasi ketergantungan diantara variable tersebut.<br> Tugas Akhir ini bertujuan untuk menganalisis performansi waktu klasifikasi dan akurasi dari Bayesian Network (BN) Classifier pada Naïve Bayes dan TAN Classifier yang pemodelannya dibangun menggunakan algoritma conditional independence test.<br>Kata Kunci : Kata Kunci: Bayesian Network Classifier, klasifikasi, data mining. Conditional independence test, Naïve Bayes, TAN.<br>ABSTRACT: Data mining is a process to find out the potential of information implicitly from database which unknown identifier before. One of many tasks in data mining that would be the subject of this final project is classification, especially Bayesian Networks (BN) Classifier.<br> Bayesian Networks (BN) is a directed acyclic graph whose nodes represent variables and arcs represent statistical dependence relations among the variables and local probability distributions for each variable given values of its parents.<br> This final project analyzes the performance and accuracy of Naïve Bayes classifier and Tree Augmented Naïve Bayes classifier as classification technique of BN which build using conditional independence test based algorithms.<br>Keyword: Keywords: Bayesian Network Classifier, classification, data mining. Conditional independence test, Naïve Bayes, TAN. |
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IOS2750.113040011 |
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Telkom University |
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317 |
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library:university library |
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Perpustakaan Telkom University |
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255 |
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Katalog Library & Knowledge Center Telkom University |
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2750 |
| subject_area |
Ekonomi Program Komputer dan Teknologi Informasi Rekayasa |
| city |
BANDUNG |
| province |
JAWA BARAT |
| repoId |
IOS2750 |
| first_indexed |
2016-09-24T16:40:21Z |
| last_indexed |
2020-11-11T19:39:34Z |
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dc |
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1765819589088772096 |
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17.538404 |