| dc.contributor |
Fakultas Matematika dan Ilmu Pengetahuan Alam |
|
| dc.creator |
Istiqomah, Sarah |
|
| dc.creator |
Yanti, Teti Sofia |
|
| dc.date |
2019-01-25 |
|
| dc.date.accessioned |
2019-09-11T01:59:24Z |
|
| dc.date.available |
2019-09-11T01:59:24Z |
|
| dc.identifier |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/14551 |
|
| dc.identifier.uri |
http://hdl.handle.net/123456789/22030 |
|
| dc.description |
Abstract. Data mining is mining or discovering new information by looking for certain patterns or rules from a very large amount of data, their use has also been widely applied in various fields. Nowadays, the advancement of information technology and computers has provided data storage facilities in an electronic format so that data storage is no longer a difficult job. One of the data techniques in data mining is Market Basket Analysis, which is used to find associations between different sets of products that customers put in baskets. This thesis will discuss Market Basket Analysis using Novel Utility Frequent Itemset Mining (NUFM) algorithm on customer transactional data and Minimarket profit data at PT. XYZ City of Malang to find associations between products that are often purchased simultaneously and have high utility is measured through the values of support count, transaction weightage, and utility weightage as well as the value of confidence to show how strong the association between the two products purchased simultaneously. There were 159 transactions consisting of 63 product codes. As a result, the overall combination of itemsets is 561 frequent 2 itemsets, two products purchased simultaneously and having a high utility consist of 155 itemsets. Of the 155 itemset that have high utility, there are 31 itemsets that have strong associations based on the value of confidence. The strongest associations are "langsingin" products and "pasta gigi herbal hpai new" with product code {olg1 => dpg4} of 35.00%, so it is advisable to keep the product close together or in a certain rack to make time and energy more effective in looking for products for services in the Minimarket PT. XYZ Malang City.Keywords: Data Mining, Utility, NUFM, Support Abstrak. Data mining adalah penambangan atau penemuan informasi baru dengan mencari pola atau aturan tertentu dari sejumlah data yang sangat besar, pemanfaatannya pun sudah banyak diterapkan dalam berbagai bidang. Dewasa ini kemajuan teknologi informasi dan komputer telah menyediakan fasilitas penyimpanan data dalam format elektronik sehingga penyimpanan data bukan lagi menjadi satu pekerjaan yang sulit. Salah satu teknik data pada data mining yaitu Market Basket Analysis yang digunakan untuk menemukan asosiasi diantara himpunan produk yang berbeda yang diletakkan pelanggan dalam keranjang. Skripsi ini akan membahas Market Basket Analysis menggunakan algoritma Novel Utility Frequent Itemset Mining (NUFM) pada data transaksional pelanggan dan data profit Minimarket PT. XYZ Kota Malang untuk menemukan asosiasi diantara produk-produk yang sering dibeli secara bersamaan dan memiliki utilitas tinggi diukur melalui nilai support count, transaction weightage, dan utility weightage serta nilai confidence untuk menunjukkan seberapa besar/kuat asosiasi antara dua produk yang dibeli secara bersamaan. Terdapat 159 transaksi yang terdiri dari 63 kode produk. Hasilnya dari keseluruhan kombinasi itemsets yaitu 561 frequent 2 itemsets, dua produk yang dibeli secara bersamaan serta memiliki utilitas yang tinggi terdiri dari 155 itemsets. Dari 155 itemset yang memiliki utilitas tinggi, terdapat 31 itemsets yang memiliki asosiasi kuat berdasarkan nilai confidence. Asosiasi yang paling kuat yaitu produk “langsingin” dan “pasta gigi herbal hpai new” dengan kode produk {olg1=>dpg4} sebesar 35,00%, maka disarankan untuk menyimpan produk tersebut berdekatan atau dalam suatu rak tertentu agar lebih mengefektifkan waktu dan tenaga dalam mencari produk untuk pelayanan di Minimarket PT. XYZ Kota Malang.Kata Kunci: Data Mining, Utility, NUFM, Support |
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| dc.format |
application/pdf |
|
| dc.language |
eng |
|
| dc.publisher |
Universitas islam Bandung |
|
| dc.relation |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/14551/pdf |
|
| dc.rights |
Copyright (c) 2019 Prosiding Statistika |
|
| dc.source |
Prosiding Statistika; Vol 5, No 1, Prosiding Statistika (Februari, 2019); 32-39 |
|
| dc.source |
Prosiding Statistika; Vol 5, No 1, Prosiding Statistika (Februari, 2019); 32-39 |
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| dc.source |
2460-6456 |
|
| dc.subject |
Statistika |
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| dc.subject |
Data Mining, Utility, NUFM, Support |
|
| dc.title |
Penggunaan Algoritma Novel Utility Frequent Itemset Mining dalam Market Basket Analysis |
|
| dc.type |
info:eu-repo/semantics/article |
|
| dc.type |
info:eu-repo/semantics/publishedVersion |
|
| dc.type |
Peer-reviewed Article |
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| dc.type |
kuantitatif |
|