CD Skripsi

Market Basket Analysis Menggunakan Algoritma Apriori: Kasus Transaksi 212 Mart Soebrantas Pekanbaru

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ABSTRACT
Sales transaction data is generated every day at 212 Mart Soebrantas Pekanbaru,
so that the collected data becomes a pile of data that is rarely used. The data can
be used to define business strategies to increase sales. Data mining techniques that
can analyze the data are association rules. The method of analysis that utilizes the
association rule technique is known as Market Basket Analysis (MBA).
Determination of associations in MBA based on minimum criteria of support and
confidence. In this study will be used a priori algorithm for transaction data 212
Mart Soebrantas Pekanbaru period January-December 2020. Apriori algorithm is
an efficient algorithm for determining candidates association rules on large
amounts of data. Based on the results of the analysis found the best association
rules based on the highest lift value is the association between clothing care and
body care for group with support 6.103% and confidence 45.882%. The best
association rules for items with a minimum support of 0.50% are the Association
of Lemonilo Mie Instan Ayam Bawang 7 and Lemonilo Mie Instan Kari Ayam
with confidence 42.105% and lift 98.065.
Keywords: Data mining, market basket analysis, apriori algorithm, sales
transactions, association rule

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

03 06. 121 (0016)

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Statistika., 2021

Deskripsi Fisik

ix, 79 hlm.; ill.: 29 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

03 06. 121 (0016)

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

-

Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

ELFITRA

Versi lain/terkait

Lampiran Berkas

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