| dc.contributor |
Fakultas Matematika dan Ilmu Pengetahuan Alam |
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| dc.creator |
Nisrina, Yuyun |
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| dc.creator |
Achmad, Anneke Iswani |
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| dc.date |
2019-08-08 |
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| dc.identifier |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/17489 |
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| dc.description |
Abstract. Data mining is a technique to process data from a large database to obtain information that will help in decision making. One method on data mining is Market Basket Analysis which is used to analyse the patterns of consumer spending behavior to find associations between products in the transaction data. This paper will discuss the Market Basket Analysis using the Generalized Sequential Pattern (GSP) algorithm on the sales transaction data of PT. X in Malang city to find sequential pattern or sequence by involving transaction time measured through support value to show how big the level of dominance of an item of the whole transaction. From the sales transaction data of PT. X in the city of Malang in 2017, the transaction is conducted by as many as 58 consumers consisting of 68 types of products. Result of the data, obtained frequent 3-sequence of extra food (will 1 & 2) and Etta Goat milk (Will 1 & 2) purchased simultaneously at one time transaction, then the next transaction bought Etta Goat milk (Will 1 & 2) with the value of support of 20.69%. Keywords: Market Basket Analysis, Data Mining, Generalized Sequential Pattern, Support.Abstrak. Data mining adalah suatu teknik mengolah data dari database yang besar untuk memperoleh suatu informasi yang akan membantu dalam pengambilan keputusan. Salah satu metode pada data mining yaitu Market Basket Analysis yang digunakan untuk menganalisis pola perilaku belanja konsumen untuk menemukan asosiasi antar produk dalam data transaksi. Makalah ini akan membahas Market Basket Analysis menggunakan algoritma Generalized Sequential Pattern (GSP) pada data transaksi penjualan PT.X di Kota Malang untuk menemukan pola sekuensial atau urutan dengan melibatkan waktu transaksi yang diukur melalui nilai support untuk menunjukkan seberapa besar tingkat dominasi suatu item dari keseluruhan transaksi. Dari data transaksi penjualan PT.X di Kota Malang tahun 2017, transaksi dilakukan oleh sebanyak 58 konsumen yang terdiri dari 68 jenis produk. Hasil dari data tersebut, diperoleh frequent 3-sequence yaitu extra food (will 1 & 2) dan etta goat milk (will 1 & 2) yang dibeli secara bersamaan dalam satu waktu transaksi, kemudian transaksi selanjutnya membeli etta goat milk (will 1 & 2) dengan nilai support sebesar 20.69%.Kata Kunci: Market Basket Analysis, Data Mining, Generalized Sequential Pattern, Support. |
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| dc.format |
application/pdf |
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| dc.language |
eng |
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| dc.publisher |
Universitas islam Bandung |
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| dc.relation |
http://karyailmiah.unisba.ac.id/index.php/statistika/article/view/17489/pdf |
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| dc.rights |
Copyright (c) 2019 Prosiding Statistika |
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| dc.source |
Prosiding Statistika; Vol 5, No 2, Prosiding Statistika (Agustus, 2019); 63-69 |
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| dc.source |
Prosiding Statistika; Vol 5, No 2, Prosiding Statistika (Agustus, 2019); 63-69 |
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| dc.source |
2460-6456 |
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| dc.subject |
Statistika |
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| dc.subject |
Market Basket Analysis, Data Mining, Generalized Sequential Pattern, Support. |
|
| dc.title |
Market Basket Analysis Menggunakan Algoritma Generalized Sequential Pattern (Kasus Data Transaksi Penjualan PT.X di Kota Malang Tahun 2017) |
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| dc.type |
info:eu-repo/semantics/article |
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| dc.type |
info:eu-repo/semantics/publishedVersion |
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| dc.type |
Peer-reviewed Article |
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| dc.type |
Kuantitatif |
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