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MINIMARKET SALES OPTIMIZATION: IMPLEMENTATION OF FPGROWTH ALGORITHM AND MONGODB WITH PYTHON

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ABSTRAK
Abstract This study applies an integrated FP-Growth algorithm with MongoDB and Python to analyze 150,000 minimarket transaction records over a one-year period. The dataset includes transaction numbers, product names, quantities sold, transaction dates, purchase prices, and selling prices. The parameters of a minimum support of 0.001, a confidence of 0.01, and a lift above 1.0 are used to ensure relevant association rules. The analysis indicates that the discovered product association patterns can increase operational efficiency by up to 15%, particularly
in instant food and ready-to-drink beverage categories. These data driven strategies also boost sales volume by 12.3% and reduce dead stock by 8.7%. Beras MCS 5KG stands out as the most profitable product, with a margin of IDR
1,066,724,400. The main strength of this study lies in the integration of FPGrowth with MongoDB, enabling large-scale real-time analysis without generating candidate itemsets. This approach enhances data processing efficiency, allowing minimarkets to optimise inventory and promotional strategies more accurately.Kata Kunci : FP-Growth, MongoDB, Python, Minimarket, Sales

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

Jurnal/S1/TI/04/KUR/2025

Penerbit

Bandung : STMIK - IM., 2025

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

2527-9866

Klasifikasi

NONE

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

VOL. 10, NO. 1, MARET 2025

Subjek

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Info Detail Spesifik

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Pernyataan Tanggungjawab

STMIK-IM

Versi lain/terkait

Lampiran Berkas

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