Rekomendasi Paket Menu Pada Kopi Mesra Abadi Menggunakan Algoritma FP-Growth dan K-Means

Arrasyid, Nizar Maulana (2025) Rekomendasi Paket Menu Pada Kopi Mesra Abadi Menggunakan Algoritma FP-Growth dan K-Means. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

The decline in sales that occurred at Kopi Mesra Abadi from a surplus of 131.6% in October 2023 to 37.96% in March 2024 has an impact on the achievement of the company's targets. This indicates the need for a more effective promotional strategy to increase sales. This study uses two main algorithms to analyze customer purchasing patterns and design menu packages. The FP-Growth algorithm is used to find Frequent Itemsets and Association Rules, which help identify menu combinations that are often purchased together. Meanwhile, K-Means Clustering is used to group customers into three clusters based on the time of purchase at each session (Session 1: 09.00-13.59, Session 2: 14.00-16.59, Session 3: 17.00-23.59). Each session is analyzed to produce menu package recommendations that match customer preferences at a certain time. The results of the study indicate that dividing customers into three clusters per session in designing relevant menu packages. For example, in Session 1 Cluster 0 often buys "Spicy Chicken Rice" and "Teh O" for personal lunch package recommendations, while Session 2 Cluster 2 prefers "Salted Chicken Rice with Egg" and "Mawut Fried Rice" for home-office package recommendations. In Session 3 Cluster 2 recommendations such as the Executive Meeting Package consisting of "Butter Coffee + Caramel Coffee + Baileys Coffee" are suitable for executive meetings. This study concludes that the application of FP-Growth and K-Means can provide a strong basis in designing menu package recommendations to increase promotional appeal and achieve predetermined sales targets.

Item Type:

Thesis (Undergraduate)

Contributors:

Contribution	Contributors	NIDN/NIDK	Email
Thesis advisor	Wahyuni, Eka Dyar	NIDN0001128406	ekawahyuni.si@upnjatim.ac.id
Thesis advisor	Arifiyanti, Amalia Anjani	NIDN0712089201	amalia_anjani.fik@upnjatim.ac.id

Subjects:

T Technology > T Technology (General)

Divisions:

Faculty of Computer Science > Departemen of Information Systems

Depositing User:

Nizar Maulana Arrasyid

Date Deposited:

26 May 2025 03:52

Last Modified:

26 May 2025 03:52

URI:

https://repository.upnjatim.ac.id/id/eprint/36486