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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi J-CEKI
Ramadhani, Devika Azahra
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Penerapan Data Mining Menggunakan Algoritma Apriori pada Brand Milenials Cafe Gunawan, Hadi; Tundo, Tundo; Ramadhani, Devika Azahra; Waloeya, Farhan Adriansyah
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp215-221

Abstract

Millennials Café is a cafe that just opened in March 2024, in an effort to stay relevant and competitive in this field, Millennials Café needs to continue to innovate and adjust to customer preferences. One way is to utilize data mining technology. The Apriori algorithm is one of the data mining technologies that can be used. The application of the apriori algorithm to the Milenials Café transaction data aims to find association rules to be able to generate frequencies and relationships between one or more items in the transaction data in the Milenials Café. This research produces 33 association rules that can help the sales strategy at Milenials Café. The following are the association rules with the highest confidence value, namely the Thai Tea menu, Milo Dinasourus, 100% Millennials Pizza, Hezelnut Chocolate, Oreo Cookies and Cream Shake 97%. Millennials Pizza, Fried Potatoes 96%. The 33 rules that already exist can be used as a reference for the owner of Millennials Café to create a sales strategy that can increase cafe revenue.
Analisis Rule-Based dengan Algoritma Apriori untuk Menu Unggulan Kedai Kopi Ramadhani, Devika Azahra
J-CEKI : Jurnal Cendekia Ilmiah Vol. 4 No. 6: Oktober 2025
Publisher : CV. ULIL ALBAB CORP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56799/jceki.v4i6.11276

Abstract

Penelitian ini bertujuan untuk menerapkan algoritma Apriori melalui analisis berbasis aturan (rule-based analysis) guna mengidentifikasi perbandingan menu unggulan di kedai kopi. Dalam lingkungan bisnis yang kompetitif, manajemen menu yang efektif sangat penting untuk meningkatkan kepuasan pelanggan dan memaksimalkan keuntungan. Algoritma Apriori digunakan untuk menganalisis pola pembelian produk kopi yang sering dibeli secara bersamaan, sehingga dapat mengungkap kombinasi menu yang lebih disukai. Data penelitian diperoleh dari transaksi penjualan menu kedai kopi dalam periode tertentu. Aturan yang dihasilkan dari penerapan algoritma Apriori kemudian dianalisis untuk menilai asosiasi antarproduk yang sering dibeli bersamaan. Hasil penelitian ini diharapkan dapat mengidentifikasi menu unggulan yang berpotensi meningkatkan penjualan serta menyesuaikan dengan preferensi pelanggan. Penelitian ini juga berkontribusi dalam pengambilan keputusan menu yang lebih efektif di kedai kopi serta menjadi referensi bagi strategi pemasaran dan manajemen produk.
Penerapan Data Mining Menggunakan Algoritma Apriori pada Brand Milenials Cafe Gunawan, Hadi; Tundo, Tundo; Ramadhani, Devika Azahra; Waloeya, Farhan Adriansyah
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp215-221

Abstract

Millennials Café is a cafe that just opened in March 2024, in an effort to stay relevant and competitive in this field, Millennials Café needs to continue to innovate and adjust to customer preferences. One way is to utilize data mining technology. The Apriori algorithm is one of the data mining technologies that can be used. The application of the apriori algorithm to the Milenials Café transaction data aims to find association rules to be able to generate frequencies and relationships between one or more items in the transaction data in the Milenials Café. This research produces 33 association rules that can help the sales strategy at Milenials Café. The following are the association rules with the highest confidence value, namely the Thai Tea menu, Milo Dinasourus, 100% Millennials Pizza, Hezelnut Chocolate, Oreo Cookies and Cream Shake 97%. Millennials Pizza, Fried Potatoes 96%. The 33 rules that already exist can be used as a reference for the owner of Millennials Café to create a sales strategy that can increase cafe revenue.
Co-Authors Hadi Gunawan, Hadi Tundo, Tundo Waloeya, Farhan Adriansyah