Skripsi

ASOSIASI PEMBELIAN BARANG KERIPIK DAN KERUPUK MENGGUNAKAN ALGORITMA APRIORI

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MSMEs need to understand consumer behavior and improve business efficiency through transaction data analysis. This research focuses on purchasing patterns for chips and crackers products using the Apriori algorithm on transaction data for Rizan 858 Snack MSMEs. The transaction data includes 200 transactions recorded between October 2023 and May 2024. The analysis process was conducted in several stages, including data collection, preprocessing, and the application of the Apriori algorithm with Minimum Support parameters of 0.05, 0.1, and 0.15 and Minimum Confidence parameters of 0.3, 0.4, and 0.5. The results show that a Minimum Support of 0.05 and Minimum Confidence of 0.5 produced an average Lift value of 2.753, which provides the best association patterns. One of the discovered patterns is the product combination ['Makaroni', 'Kerupuk Udang Melati'] → ['Stick Keju', 'Kerupuk Jengkol'] with a Confidence value of 68.42% and the highest Lift reaching 5.2632. This pattern indicates a strong relationship between products, which can be utilized to develop marketing strategies such as product bundling, stock optimization, and more efficient distribution, ultimately supporting the sustainable growth of MSMEs.

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Detail Information

Series Title

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Call Number

T1626962024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xvi, 124 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.015 107

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

-

Subject(s)

Prodi Teknik Informatika
Prinsip Matematika dalam Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

MURZ

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