Rifa'i, Irfa Ahmad (2025) IMPLEMENTASI DATA MINING UNTUK MENGANALISIS POLA PEMBELIAN KONSUMEN DENGAN ALGORITMA FP-GROWTH PADA TSANGOO RICE TO GO AND JUICE BAR. S1 / D3 thesis, Universitas Kuningan.

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Official URL: https://rama.uniku.ac.id

Abstract

Persaingan industri Food and Beverage (FnB) yang semakin ketat di Kabupaten Kuningan berdampak pada penurunan penjualan di Tsangoo Rice To Go and Juice Bar. Selain itu, penumpukan data transaksi penjualan yang belum dikelola secara optimal menyebabkan kesulitan dalam proses analisis dan pengambilan keputusan manajerial. Penelitian ini bertujuan untuk membangun sistem berbasis web yang mampu menganalisis pola pembelian konsumen menggunakan algoritma Frequent Pattern Growth (FP-Growth). Metode FP-Growth digunakan untuk menemukan asosiasi antar produk berdasarkan data transaksi penjualan. Sistem ini dikembangkan dengan bahasa pemrograman PHP dan database MySQL. Hasil implementasi menunjukkan bahwa sistem berhasil mengidentifikasi pola pembelian konsumen berdasarkan nilai minimum support dan confidence yang telah ditentukan. Sebagai contoh, ditemukan hubungan antara produk Beef dan Jasmine Tea dengan nilai support sebesar 10% dan confidence sebesar 38,46%, serta lift ratio sebesar 2,26. Temuan ini dapat dimanfaatkan sebagai dasar strategi bisnis, seperti pembuatan promo bundling berdasarkan pola pembelian. Dengan adanya sistem ini, Tsangoo dapat memperoleh wawasan yang lebih mendalam terkait tren pembelian konsumen, sehingga mendukung pengambilan keputusan strategis dalam upaya meningkatkan penjualan dan daya saing bisnis.

The increasing competition in the Food and Beverage (FnB) industry in Kuningan Regency has led to a decline in sales at Tsangoo Rice To Go and Juice Bar. Additionally, the accumulation of unorganized sales transaction data has hindered effective analysis and managerial decision-making. This research aims to develop a web-based system capable of analyzing consumer purchasing patterns using the Frequent Pattern Growth (FP-Growth) algorithm. The FP-Growth method is used to discover associations between products based on sales transaction data. The system was developed using PHP programming language and MySQL database. The implementation results show that the system successfully identifies purchasing patterns based on predefined minimum support and confidence values. For example, a relationship was found between the Beef and Jasmine Tea products with a support value of 10% and a confidence value of 38.46%, along with a lift ratio of 2.26. These findings can be utilized as the basis for business strategies, such as creating promotional bundles based on identified purchase patterns. This system provides Tsangoo with deeper insights into consumer purchasing trends, supporting strategic decision-making efforts to improve sales performance and business competitiveness.

Item Type: Thesis (S1 / D3)
Uncontrolled Keywords: Data Mining, FP-Growth, Pola Pembelian. Data Mining, FP-Growth, Purchase Pattern.
Subjects: Z Bibliography. Library Science. Information Resources > ZA Information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources
Divisions: Fakultas Ilmu Komputer > S1 Sistem Informasi
Depositing User: S. Kom Irfa Ahmad Rifa'i
Date Deposited: 06 Oct 2025 07:23
Last Modified: 06 Oct 2025 07:23
URI: https://rama.uniku.ac.id/id/eprint/3375

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