๐Ÿ“… 12 July 2024
DOI: 10.51903/elkom.v17i1.1759

Analisa Data Mining Menggunakan Algoritma Apriori Dan Algoritma Eclat Di PT Astra International BMW Semarang

Jurnal Elektronika dan Komputer
Universitas Sains dan Teknologi Komputer

๐Ÿ“„ Abstract

PT Astra International BMW Semarang operates in the automotive sector, focusing on sales, aftersales, and spare parts for BMW cars. The availability of spare parts is crucial for customer satisfaction, as stock shortages can lead to disappointment. Using data from 52,162 spare parts sales transactions from January 2019 to June 2023, the study applies data mining techniques with the a priori and eclat algorithms to identify consumer purchasing patterns and prevent stock shortages. The research aims to provide recommendations for prioritizing spare parts stock. Utilizing the CRISP-DM methodology and R programming, the study found that the highest confidence in purchasing patterns occurs with a combination of three itemsets: if a customer buys an oil filter set (B11.42.8.593.186) and washer cleaner (B83.12.5.A1A.683), they will also buy BMW engine oil (Z99000000333) with 100% confidence. These findings can help PT Astra International BMW Semarang manage spare parts stock more effectively.

๐Ÿ”– Keywords

#Data Mining; Association; Apriori Algorithm; Eclat Algorithm

โ„น๏ธ Informasi Publikasi

Tanggal Publikasi
12 July 2024
Volume / Nomor / Tahun
Volume 17, Nomor 1, Tahun 2024

๐Ÿ“ HOW TO CITE

Dimas Bayu Wardana; Sulastri Sulastri, "Analisa Data Mining Menggunakan Algoritma Apriori Dan Algoritma Eclat Di PT Astra International BMW Semarang," Jurnal Elektronika dan Komputer, vol. 17, no. 1, Jul. 2024.

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