The Menu Clustering At Doktor Kopi Using K-Means Algorithm To Increase Sales

  • Septian Simatupang Department of Software Engineering Technology, Polytechnic Wilmar Bisnis Indonesia
  • Monsyah Juansen Faculty of Engineering, Information Systems Study Program, University Muhammadiyah Bengkulu, Indonesia
  • Rizki Ramadhansyah Department of Software Engineering Technology, Polytechnic Wilmar Bisnis Indonesia
  • Taufiqurrahman Department of Software Engineering Technology, Polytechnic Wilmar Bisnis Indonesia
  • Windi Saputri Simamora Informatics Program Study, Faculty of Technology and Computer Science, Universitas Satya Terra Bhinneka, Indonesia
Keywords: Clustering, K-Means, Coffee Doctor, Sales.

Abstract

Coffee Doctoris a coffee shop with a variety of menus and a strategic location in Medan City, this coffee shop is currently developing a strategy to increase sales of their products. Effective menu arrangement is an important factor in increasing product sales in coffee shops or cafes. This study aims to optimize sales by utilizing the K-Means algorithm to group menus based on customer purchasing patterns. The sales data analyzed includes product types, purchase frequency, and revenue contributions from each menu. Through the clustering process, menus can be grouped into several categories, such as the best-selling, medium and less popular menus. The results of this clustering are used to design a more structured menu arrangement strategy, such as arranging menu positions on the list, special promotions, or eliminating less effective menus. The implementation of the K-Means algorithm shows that a data-based menu arrangement strategy can improve customer experience and significantly drive product sales. Thus, this study provides a practical contribution for coffee shop or cafe managers to optimize sales through a technology and data-based approach.

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References

3855-Article Text-14663-2-10-20220523. (nd).
Amin, F., Anggraeni, DS & Aini, Q. (2022). Application of K-Means Method in Souq.Com Product Sales. Applied Information System and Management (AISM), 5(1), 7–14. https://doi.org/10.15408/aism.v5i1.22534
Data Mining Analysis on UMKM Clustering Using the K-Means Algorithm. (nd).
Anggraeni, Y. & Handayani, P. (2023). Application of K-Means Method to Determine Swimming Ticket Sales at Splash Swimming Pool & Gym. Journal of Informatics and Information Technology, 2(1). https://doi.org/10.56854/jt.v2i1.167
Ardiyasa, IW (2020). Application of K-Means Clustering for Cyber Attack Classification on Syslog File. Journal of Systems and Informatics (JSI), 14(2), 143–149. https://doi.org/10.30864/jsi.v14i2.305
Fachriansyah, A. & Bu'ulolo, E. (2023). Application of K-Means Algorithm for Clustering Bakery and Cake That Sells Well. Bulletin of Information Technology (BIT), 4(2), 205–217. https://doi.org/10.47065/bit.v3i1
Hasibuan, FPA, Sumarno, S. & Parlina, I. (2021). Application of K-Means in Smartphone Product Sales Grouping. SATESI: Journal of Science, Technology and Information Systems, 1(1), 15–20. https://doi.org/10.54259/satesi.v1i1.3
Juliana, E. & Vivi Nur Aleyda, and. (2021). APPLICATION OF K-MENS CLUSTERING METHOD TO HELP DETERMINE THE LEVEL OF STATUS OF COVID 19 IMPACT REGIONS (Vol. 12, Issue 1). https://jurnal.umj.ac.id/index.php/just-it/index
Kesuma Dinata, R., Hasdyna, N. & Azizah, N. (2020). K-Means Clustering Analysis on Motorcycle Data. In Informatics Journal (Vol. 5, Issue 1).
Lili, A., Cipta, H. & Widodo, S. (2022). Grouping of Oil Palm Harvest Results in Production Per Block Using the K-Means Algorithm. In Journal of Machine Learning and Data Analytics (MALDA) (Vol. 01, Issue 01).
Mega, W. (2015). CLUSTERING USING K-MEANS METHOD TO DETERMINE NUTRITIONAL STATUS OF TODDLERS (Vol. 15, Issue 2).
Muliono, R. & Sembiring, Z. (2019). DATA MINING CLUSTERING USING K-MEANS ALGORITHM FOR CLUSTERIZATION OF LECTURERS' TEACHING TRIDARMA LEVELS (Vol. 4, Issue 2).
By. (nd). THE USE OF K-MEANS ALGORITHM IN DETERMINING MAJORS FOR HIGH SCHOOL (CASE STUDY AT STATE SENIOR HIGH SCHOOL 1 JAKARTA).
Application of K-Means Clustering in Data Grouping (Case Study of Mathematics Student Profile, FMIPA UNM). (nd). http://www.ojs.unm.ac.id/jmathcos
Application_of_Data_Mining_in_Improving_the_Quality_of_Education. (nd).
Saputra, EA & Nataliani, Y. (2021). Analysis of Student Grade Data Grouping to Determine High Achieving Students Using the K-Means Clustering Method. Journal of Information Systems and Informatics, 3(3). http://journal-isi.org/index.php/isi
Saputra, TI & Arianty, R. (2019). IMPLEMENTATION OF K-MEANS CLUSTERING ALGORITHM IN INDOSAT USER COMPLAINT SENTIMENT ANALYSIS. Scientific Journal of Computer Informatics, 24(3), 191–198. https://doi.org/10.35760/ik.2019.v24i3.2361
Selvi, C., Sembiring, D., Hanum, L. & Parsaoran Tamba, S. (2022). APPLICATION OF DATA MINING USING K-MEANS ALGORITHM TO DETERMINE THESIS TITLE AND RESEARCH JOURNAL (CASE STUDY OF FTIK UNPRI). Journal of Information Systems and Computer Science Prima), 5(2).
Sibuea, FL & Sapta, A. (2017). MAPPING OF HIGH-ACHING STUDENTS USING THE K-MEANS CLUSTERING METHOD. 1, 85–92.
Zakiyah, D., Merlina, N. & Mayangky, NA (nd). Application of K-Means Clustering Algorithm to Determine IT Employee Capabilities. http://jurnal.bsi.ac.id/index.php/co-science
Published
2024-12-31
How to Cite
Septian Simatupang, Monsyah Juansen, Rizki Ramadhansyah, Taufiqurrahman, & Windi Saputri Simamora. (2024). The Menu Clustering At Doktor Kopi Using K-Means Algorithm To Increase Sales. INFOKUM, 12(04), 73-84. Retrieved from https://infor.seaninstitute.org/index.php/infokum/article/view/2778