Analisis Pola Konsumen Dalam Bertransaksi Bisnis di Bengkel Resmi AHASS Total Honda Motor

Budi  Wardoyo; Puji Winar Cahyo; Muhammad Habibi; M. Abu Amar Al Badawi

doi:10.30989/teknomatika.v16i1.1133

Budi Wardoyo
Puji Winar Cahyo
Muhammad Habibi
M. Abu Amar Al Badawi Universitas Jenderal Achmad Yani Yogyakarta

DOI: https://doi.org/10.30989/teknomatika.v16i1.1133

Abstract

The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.

References

[1] J. E. Tjhandra and Y. Widiastiwi, “IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK MENENTUKAN FREQUENT ITEM SET PADA PENYEDIAAN SPARE PART (STUDI KASUS: BENGKEL RESMI YAMAHA ANUGERAH MOTOR),” Universitas Pembangunan Nasional Veteran Jakarta, 2019.

[2] A. F. Afif, E. R. Swedia, and M. Cahyanti, “Implementasi Algoritma Association Rule Untuk Promosi Produk Berbasis Website Pada Bengkel Delta Jaya Motor,” Jurnal Ilmiah Teknologi dan Rekayasa, vol. 24, no. 2, pp. 152–160, 2020.

[3] G. Guntoro and C. P. Hutabarat, “Penerapan Data Mining Association Rule Menggunakan Algoritma FP-Growth Untuk Persediaan Sparepart pada Bengkel,” Jurnal Komtika (Komputasi dan Informatika), vol. 5, no. 2, pp. 112–121, 2021.

[4] J. Han, M. Kamber, and J. Pei, “Data mining concepts and techniques third edition,” University of Illinois at Urbana-Champaign Micheline Kamber Jian Pei Simon Fraser University, 2012.