cover
Contact Name
Muhammad Fadlan
Contact Email
fadlan@ppkia.ac.id
Phone
+6281216123988
Journal Mail Official
jbidai@ppkia.ac.id
Editorial Address
Kampus STMIK PPKIA Tarakanita Rahmawati, Jl. Halmahera 99 Oval Ladang IV Tarakan 77113 – Kalimantan Utara
Location
Kota tarakan,
Kalimantan utara
INDONESIA
Journal of Big Data Analytic and Artificial Intelligence
ISSN : 25979604     EISSN : 27223256     DOI : https://doi.org/10.71302
Core Subject : Science,
JBIDAI adalah jurnal nasional berbahasa Indonesia versi online yang dikelola oleh Prodi Sistem Informasi STMIK PPKIA Tarakanita Rahmawati. Jurnal ini memuat hasil-hasil penelitian dengan cakupan fokus penelitian meliputi : Artificial Intelligence, Big Data, Data Mining, Information Retrieval, Knowledge Doscovering in Database dan bidang-bidang lainnya yang termasuk ke dalam rumpun ilmu tersebut.
Articles 41 Documents
Pengaturan Tata Letak Produk Fashion dengan FP-Growth untuk Peningkatan Penjualan UMKM Widyasari; Syafiqoh, Ummi; Rahmadania, Nova Tari; Hartono, Lies
Journal of Big Data Analytic and Artificial Intelligence Vol 8 No 1 (2025): JBIDAI Juni 2025
Publisher : STMIK PPKIA Tarakanita Rahmawati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71302/jbidai.v8i1.69

Abstract

The application of data mining techniques in the business sector contributes significantly to strategic decision-making. This study implements the FP-Growth algorithm to analyze consumer purchasing patterns at Zaynthary Store, a fashion retail shop located in Tarakan City. A total of 161 sales transaction records were collected and processed to identify frequent itemsets and association rules that represent relationships between products. The findings reveal that certain item combinations are frequently purchased together, such as {Blouse → Jeans} with a confidence value of 55%, suggesting that these items should be placed near each other in the store display layout. FP-Growth has proven effective in exploring customer purchase patterns and providing layout recommendations that can support increased sales. These results can serve as a strategic reference for designing data-driven store layouts in the fashion retail industry.