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ITS » Undergraduate Theses » Teknik Informatika
Posted by dewi007 at 30/12/2009 16:58:12  •  4843 Views


PENGGALIAN KAIDAH ASOSIASI MENGGUNAKAN METODE APRIORI-TFP PADA STRUKTUR DATA T-TREE DAN P-TREE

ASSOCIATION RULE MINING USING THE APRIORI-TFP METHOD ON T-TREE AND P-TREE DATA STRUCTURES

Author :
Karim, Farid Abdul ( 5100100012 )




ABSTRAK

Penggalian kaidah asosiasi mempunyai peranan penting dalam proses pengambilan keputusan. Tahapan besar dari proses ini adalah mengidentifikasikan frequent itemset dan membentuk kaidah asosiasi dari itemset tersebut. Kaidah asosiasi digunakan untuk menggambarkan hubungan antar item pada data transaksional. Namun karena sangat besarnya data transaksional yang biasa digunakan dalam praktek. Maka diperlukan suatu metode yang efisien guna mengoptimalkan waktu proses yang dibutuhkan. Dalam Tugas Akhir ini dibuat aplikasi data mining untuk pencarian kaidah asosiasi menggunakan metode Apriori-TFP Total from Partial. metode ini dimulai dengan proses pembangkitan P-Tree untuk membentuk sebuah tree berdasarkan hasil pembacaan basis data per transaksi. Semakin banyak transaksi yang terlibat maka semakin besar dan rumit bentuk tree yang terbuat. Hasil pembentukan P-Tree digunakan dalam proses. Transformasi P-Tree menjadi P-Tree table yang dibentuk berdasarkan tingkatan dari masing-masing item. Selanjutnya table ini dijadikan sebagai masukan untuk proses pencarian kaidah asosiasi. Aplikasi dilakukan berbagai uji coba.dari seluruh uji coba yang telah dilakukan dapat disimpulkan semakin kecil nilai minimuk support yang ditentukan akan mengakibatkan waktu komputasi secara total akan semakin lama. Begitu juga jika jumlah item dan jumlah transaksi yang terlibat semakin besar maka akan mengkibatkan waktu komputasi dan kebutuhan memory akan semakin meningkat. Selain itu uji coba aplikasi ini membutuhkan waktu komputasi yang jauh lebih cepat dibandingkan dengan aplikasi yang menggunakan metode Apriori.


ABSTRACT

Association rule mining plays an important role in a decision making process. The main task of an association rules mining involves a process for identifying frequent itemsets prior to a process of generating association rules. These association rules are used to describe the relationship among items contained in the transactional data. However due to the large number of transactional data that must be processed an efficient method for identifying frequent itemsets and generating the association rules is required to reduce the overal computing time. In this finel project an aplication of data mining for generating association rules is implemented using the apriori-TFP Total from Partial. In this method a P-Tree generation is first conducted to build a tree based on result of the database scan of the transactional data. The more the data that must be processed the more complicated tree will be produced. Based on the level of each item contained in T-Tree a P-Tree Table is then transformed accordingly. Finally the resulting P-Tree Table is used as an input to a process of association rules mining. The application that has been implemented was tested agains several transactional data. The experimental result show that the smaller the minimum support value the longer the total computing time required. Similary the larger the number of items and transactions the larger the amount of memory consumed. In compared to the epriori method the application runs significantly faster than that of the apriori method.



KeywordsT-Tree ; P-Tree ; Apriori-TFP ; Kaidah Asosiasi
 
Subject:  Perangkat lunak komputer
Contributor
  1. Prof.Dr.Ir Arief Djunaidy, M.sc
    Darlis Herumurti, S.kom
Date Create: 30/12/2009
Type: Text
Format: pdf.
Language: Indonesian
Identifier: ITS-Undergraduate-3100007028759
Collection ID: 3100007028759
Call Number: RSIf 005.73 Kar p


Source
Undergraduate Theses of Informatics Engineering, RSIf 005.73 Kar p, 2007

Coverage
ITS Community Only

Rights
Copyright @2007 by ITS Library. This publication is protected by copyright and permission should be obtained from the ITS Library prior to any prohibited reproduction, storage in a retrievel system, or transmission in any form or by any means, electronic, mechanical, photocopying, recording, or likewise. For information regarding permission(s), write to ITS Library




[ Download - Open Access ]

  1.  ITS-Undergraduate-6735-5100100012-kesimpulan.pdf - 27 KB




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