📅 03 January 2026
DOI: 10.51903/tc3ne886

Implementasi Algoritma FP-Growth Untuk Menemukan Pola Hubungan Antar Barang pada Transaksi Penjualan

JUISI : Jurnal Ilmiah Sistem Informasi
Universitas Sains dan Teknologi Komputer

📄 Abstract

This study is motivated by the problem faced by Toko Polirindo, where sales transaction data are stored only as archives and have not been utilized for analytical purposes, resulting in unstable product availability, recurring stock shortages, and difficulties in predicting customer purchasing behavior; therefore, this research aims to identify patterns of item associations that frequently occur together by applying the Association Rule Mining method using the FP-Growth algorithm, which is recognized for its ability to extract frequent itemsets efficiently without the need to generate candidate combinations as in the Apriori algorithm. The dataset consists of sales transactions recorded from January to September 2025. It undergoes several stages, including preprocessing, binary transformation, and analysis using RapidMiner to generate frequent itemsets and association rules, evaluated using support, confidence, and lift metrics. The results reveal that item 3 consistently appears as the most dominant consequent across almost all generated rules, with confidence values ranging from 0.322 to 0.347, indicating that this item is most strongly associated with other items and frequently appears as a complementary product in customer transactions. These findings provide practical contributions by offering insights to optimize stock management, improve product placement, and develop promotional strategies based on actual purchasing patterns, while also demonstrating that the FP-Growth algorithm is an effective analytical tool to support data-driven decision-making aimed at enhancing operational efficiency and customer satisfaction in retail environments.

🔖 Keywords

#FP-Growth Algorithm; Association Rule Mining; Frequent Itemset; Sales Transaction Analysis; Data Mining; Algoritma FP-Growth; Aturan Asosiasi; Frequent Itemset; Analisis Transaksi Penjualan; Data Mining

ℹ️ Informasi Publikasi

Tanggal Publikasi
03 January 2026
Volume / Nomor / Tahun
Volume 4, Nomor 2, Tahun 2026

📝 HOW TO CITE

Nadia, Nadia; Tripasha, Ghina; Atya, Nur; Sutejo, Heru; Nadia, Nadia; Tripasha, Ghina ; Atya, Nur ; Sutejo, Heru, "Implementasi Algoritma FP-Growth Untuk Menemukan Pola Hubungan Antar Barang pada Transaksi Penjualan," JUISI : Jurnal Ilmiah Sistem Informasi, vol. 4, no. 2, Jan. 2026.

ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
DOI

🔗 Artikel Terkait dari Jurnal yang Sama

Design and Implementation of a Web-Based QR Code Employee Attendance System for Optimizing Attendance Management: A Case Study at Bento and Es Teh Luwes Ungaran

Nufninu, Novinda Grezen; Rudjiono, Rudjiono; Panjaitan, Cherlina Helena Purnamasari ; Nufninu, Novinda Grezen; Rudjiono, Rudjiono; Panjaitan, Cherlina Helena Purnamasari

21 May 2026

Deteksi Aktivitas Vape Berbasis Yolov8 pada Citra dan Video dengan Pendekatan Deep Learning

Lahuddin, Lahuddin; Larasati, Pamela ; Hasbi, Abdilah; Lahuddin, Lahuddin; Larasati, Pamela ; Hasbi, Abdilah

21 May 2026

Grouping of Student Attendance Discipline Levels Based on Daily Attendance Data Using the K-Means Algorithm

Putri, Syahwa Mutiara ; Rahmawati, Anita; Bella, Alfina Chintya; Gurowo, Damar Aji; Arifin, Muhammad; Putri, Syahwa Mutiara ; Rahmawati, Anita; Bella, Alfina Chintya ; Gurowo, Damar Aji; Arifin, Muhammad

21 May 2026

Sistem Informasi Penerimaan Jasa Tenaga Kerja Berbasis Website dengan Metode Extreme Programming (Studi Kasus PT: Gunung Batu)

Pramudya, Bagas; Ariati, Nining ; Dhamayanti, Dhamayanti; Pramudya, Bagas; Ariati, Nining ; Dhamayanti, Dhamayanti

21 May 2026

Analisis Perbandingan Yolov11 dan MobileNetV3 untuk Klasifikasi Varietas Padi

Octaviansyah, Ade ; Sari, Herva Emilda; Raharjo, Teguh; Octaviansyah, Ade; Sari, Herva Emilda ; Raharjo, Teguh

21 May 2026

UI/UX Design of a Mobile Application for Shoe Cleaning Service Management Using the Design Thinking Method (Case Study: OurShoes)

Cahyani, Clariesta Eka Nanda ; Voutama, Apriade ; Cahyani, Clariesta Eka Nanda ; Voutama, Apriade

21 May 2026

📊 Statistik Sitasi Jurnal