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ITS » Master Theses » Matematika - S2
Posted by aprill@is.its.ac.id at 10/12/2015 07:31:00  •  1481 Views


RULE-BASED NEURAL NETWORKS PADA DATA MINING UNTUK MARKET BASKET ANALYSIS

Author :
ASTUTI, YULIANI PUJI ( 1203201 004 )




ABSTRAK

Era perdagangan bebas menuntut para produsen untuk selalu meningkatkan daya saing. Selain dengan meningkatkan mutu produk para produsen juga harus memperhatikan mutu layanan terhadap konswnen. Mutu pelayanan dapat ditingkatkan dengan cara mempermudah konsumen dalam berbelanja dan mendapatkan barang yang dibutuhkannya. Seorang manajer pemasaran membutuhkan informasi yang diperoleh dari pola keterkaitan antar sejwnJah produk dari data histori. Pola yang diperoleh dapat dijadikan acuan untuk mengenali perilaku konsumen membaca kecenderungan selera pasar masa depan serta untuk mendapatkan pasar bam. Data mining khususnya untuk market basket analysis dapat membantu mengetahui pola keterkaitan antar produk yang dibeli oleh konswnen dalam bentuk association rules. Association rules tersebut dapat dijadikan pedoman penentuan tata letak produk yang memudahkan konsumen untuk mendapatkannya secara bersamaan. Dalam tesis ini digunakan rule-based neural networks RBNN sebagai metode untuk mendapatkan association rules dan membandingkannya dengan perhitungan confidence. Melalui training sebanyak 3500 data transaksi RBNN berhasil mendapatkan afsociation rules yang mendekati perhitungan confidence sehingga dapat digunakan untuk Market Basket Analysis.


ABSTRACT

In this free trade era all producers have to improve their competitiveness. Besides by upgrading product all producers also have to pay attention to quality of service to consumer. Quality of service can be improved by watering down consumer in shopping and getting goods required. A marketing manager require the information obtained from related association rules of product from historical data. Pattern obtained referable to recognize the consumer behavior reading tendency of appetite of future market and also to get the new market. Data Mining specially for Market Basket Analysis can assist to know the related pattern the product composition bought by consumer in the form of association rules. the Association Rules can be made by determination guidance arrangement of the products to make consumer easier to get them concurrently. In this thesis Rule-Based Neural Networks RBNN is used as method to get the association rules and compare it with the calculation confidence. Through training as much 3500 transaction data RBNN succeed to get the association rules coming near calculation confidence so that applicable to Market Basket Analysis.



KeywordsData Mining; Market Basket Analysis; Association Ruless Rule-Based Neural Networks
 
Subject:  Jaringan saraf (ilmu komputer)
Contributor
  1. Prof. Dr. Mohammad Isa Irawan, M.T.
Date Create: 10/12/2015
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Master-12103150001561
Collection ID: 12103150001561
Call Number: RTMa 006.32 Ast r, 2005


Source
Master Theses of Mathematics, RTMa 006.32 Ast r, 2005

Coverage
ITS Community

Rights
Copyright @2015 by ITS Library. This publication is protected by copyright and per obtained from the ITS Library prior to any prohibited reproduction, storage in a re transmission in any form or by any means, electronic, mechanical, photocopying, reco For information regarding permission(s), write to ITS Library




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  1.  ITS-Master-39951-abstract_id.pdf - 224 KB
  2.  ITS-Master-39951-abstract_en.pdf - 211 KB
  3.  ITS-Master-39951-conclusion.pdf - 204 KB




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