Jurnal Algoritma, Logika dan Komputasi

Technological developments have led to significant changes in various sectors, including business. The way of trading has also gone digital through e-commerce platforms and social media. Business competition is getting tougher with the emergence of many startups. Entrepreneurs must innovate in order to survive the fierce competition. Association analysis is used in Data mining to find rules for combining items. The advantage of this technique lies in the use of efficient algorithms through high-frequency pattern analysis or frequent pattern mining. This algorithm examines candidate itemsets that evolve from the results of frequency itemsets through support-based pruning, to eliminate insignificant itemsets with a Minimum Support value of 1. The Apriori algorithm association method is used to determine item relationships and identify consumer buying patterns, as well as help entrepreneurs increase product sales. This research proves the effectiveness of the Apriori algorithm in managing transaction data and generating valuable information for companies. This research provides input to companies that want to utilize transaction data to improve business effectiveness. The main goal of the Apriori algorithm is to find itemsets that frequently co-occur in the data. The algorithm adopts a bottom-up approach, where smaller itemsets are analyzed first and larger itemsets are built from smaller itemsets. The steps in creating itemsets using the association method include problem identification, transaction data collection, itemset identification, determining the Minimum Support and confidence values, and establishing association rules. This research develops an application that calculates the Apriori algorithm with the associative method through a calculation table and a summary of the calculation results. After testing, the application shows accurate calculation results and can be checked manually. The drawback of this application is that the notification of errors in the data is only displayed one by one.

Ordila, R., Wahyuni, R., Irawan, Y., & Yulia Sari, M. (2020). Penerapan Data mining Untuk Pengelompokan Data Rekam Medis Pasien Berdasarkan Jenis Penyakit Dengan Algoritma Clustering (Studi Kasus : Poli Klinik Pt.Inecda). Jurnal Ilmu Komputer, 9(2), 148–153. https://doi.org/10.33060/jik/2020/vol9.iss2.181

Sikumbang, D. E. (2018). Penerapan Data mining Penjualan Sepatu Menggunakan Metode Algoritma Apriori. Jurnal Teknik Komputer, 4(1).

Erfina, A., Melawati, & Destria Arianti, N. (2020). Penerapan Metode Data mining Terhadap Data Transaksi Penjualan Menggunakan Algoritma Apriori (Studi Kasus: Toko Fasentro Fancy). JURSISTEKNI (Jurnal Sistem Informasi Dan Teknologi Informasi), 2(3), 14–22.

Gumilang, J. R. (2020). Implementasi Algoritma Apriori Untuk Analisis Penjualan Konter Berbasis Web. Jurnal Informatika Dan Rekayasa Perangkat Lunak (JATIKA), 1(2), 226–233. http://jim.teknokrat.ac.id/index.php/informatika

Syahdan, S. Al., & Sindar, Anita. (2018). Data mining Penjualan Produk Dengan Metode Apriori Pada Indomaret Galang Kota. Jurnal Nasional Komputasi Dan Teknologi Informasi , 1(2), 56–63.

Anjumi, K. N. (2020). Penerapan Data mining Untuk Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Apriori (Studi Kasus: Toko Diengva Bandar Jaya).

Rerung, R. R. (2018). Penerapan Data mining dengan Memanfaatkan Metode Association rule untuk Promosi Produk. Jurnal Teknologi Rekayasa, 3(1), 89. https://doi.org/10.31544/jtera.v3.i1.2018.89-98

Barkah, N., Sutinah, E., & Agustina, N. (2020). Metode Asosiasi Data mining Untuk Analisa Persediaan Fiber Optik MenggunakanAlgoritma Apriori. Jurnal Kajian Ilmiah , 20(3), 237–248. http://ejurnal.ubharajaya.ac.id/index.php/JKI

Sena Yudha, R., Auliasari, K., & Primaswara Prasetya, R. (2020). Penerapan Algoritma Apriori Untuk Menghasilkan Pola Penjualan Produk Bangunan. Jurnal Mahasiswa Teknik Informatika, 4(1), 154–161.

Prasetyo, A., Musyaffa, N., Sastra, R., Program, ], Sistem, S., Akuntansi Bogor, I., Studi, P., Komputer, T., Universitas, ], Sarana, B., Kampus Bogor, I., Stmik, ], & Mandiri, N. (2020). Implementasi Data mining Untuk Analisis Data Penjualan Dengan Menggunakan Algoritma Apriori (Studi Kasus Dapoerin’s). JURNAL KHATULISTIWA INFORMATIKA, VIII(2), 94–98.

Fahrudin, N. F. (2019). Penerapan Algoritma Apriori untuk Market basket analysis. MIND Journal | ISSN, ISSN, 1–11. https://doi.org/10.26760/mindjournal