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All Journal Jurnas Nasional Teknologi dan Sistem Informasi Internet of Things and Artificial Intelligence Journal
Widiawati, Neta Tri
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Implementation of the FP-Growth Algorithm in Sales Transactions for Menu Package Recommendations at Warung Oemah Tani Triana, Latifah Adi; Khoerida, Nur Isnaeni; Widiawati, Neta Tri; Tahyudin, Imam
Internet of Things and Artificial Intelligence Journal Vol. 2 No. 2 (2022): Volume 2, Issue 2, 2022 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.471 KB) | DOI: 10.31763/iota.v2i2.563

Abstract

Along with the rapid development of the culinary industry, business competition is also getting tougher. Warung Oemah Tani serves a variety of menus and drinks, but to provide satisfying service to customers, business people must try to develop new products. Under these circumstances, the menu recommendations for Warung Oemah Tani need to be analyzed so that the recommendations made are right on target. This study aims to analyze the sales of Warung Oemah Tani using the FP Growth algorithm. This algorithm identifies the data set with the highest frequency of concurrent sales (frequent itemset). The results of the association rules show that the highest support value is 0.520 and the highest confidence value is 0.929, with a minimum support of 30% and a minimum confidence of 80%. Obtained 14 rule associations that meet the minimum support and minimum confidence.
Penerapan Algoritma Apriori Pada Transaksi Penjualan Untuk Rekomendasi Menu Makanan Dan Minuman Merliani, Nanda Nurisya; Khoerida, Nur Isnaeni; Widiawati, Neta Tri; Triana, Latifah Adi; Subarkah, Pungkas
Jurnal Nasional Teknologi dan Sistem Informasi Vol 8 No 1 (2022): April 2022
Publisher : Departemen Sistem Informasi, Fakultas Teknologi Informasi, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/TEKNOSI.v8i1.2022.9-16

Abstract

Semakin pesatnya pertumbuhan bisnis bidang kuliner, membuat persaingan bisnis dibidang ini juga semakin ketat. Warung tenda atau yang biasanya disebut warten banyak menyajikan menu dan minuman, namun perlunya pelaku bisnis berusaha menghasilkan inovasi produk demi memberikan pelayanan memuaskan kepada pelanggan. Pada kondisi tersebut dibutuhkan sebuah teknik pengolahan data untuk mengetahui rekomendasi menu pada Warung Tenda. Metode analisis yang digunakan adalah teknik data mining dengan algoritma Apriori, dimana algoritma ini untuk mennetukan himpunan data yang paling sering muncul (frequent itemset). Hasil dari penelitian didapatkan bahwa Nilai Support dan Confidence tertinggi ialah Es Teh Manis dan Mendoan dengan nilai Support 50% dan Confidence 76%. Hal ini dapat menjadi rekomendasi kombinasi menu dari data yang telah dikumpulkan dan diterapkan algoritma apriori sehingga diharapkan dapat digunakan untuk evaluasi pelayanan serta mampu meningkatkan kepuasaan pelanggan agar Warung tenda dapat berkembang lebih pesat.
Co-Authors Imam Tahyudin Khoerida, Nur Isnaeni Merliani, Nanda Nurisya Subarkah, Pungkas Triana, Latifah Adi