ANALISIS CLUSTERING DALAM PENGELOMPOKAN PENJUALAN MENGGUNAKAN ALGORITMA K-MEANS PADA CAFE 47°COFFEE

HIDAYAT, RAIHAN (2022) ANALISIS CLUSTERING DALAM PENGELOMPOKAN PENJUALAN MENGGUNAKAN ALGORITMA K-MEANS PADA CAFE 47°COFFEE. S1 thesis, Universitas Mercu Buana.

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Abstract

Cafe 47°Coffee is one of the cafes engaged in the culinary field that provides food and drinks. With a cafe business competitor, therefore a Cafe 47°Coffee entrepreneur is needed to be able to compete in determining sales strategies by utilizing sales transaction data. The data used in this study is sales data from July 2021 to February 2022. Cafe 47°Coffee entrepreneurs utilize Data Mining to help make sales strategy decisions in order to find out which products need to be improved and provide solutions for decision makers, one of the methods used is The method used is the clustering method using the K-Means algorithm. The Cafe 47°Coffee entrepreneurs group their products into 3 criteria, namely very selling, selling well, and not selling well. The data is processed by manual calculations and using the Rapid Miner tool to perform the test, so that the final results are in the form of 4 cluster items that are very selling, namely V60, Caramel Coffee Latte, Red Velvet, and Chocolate, 7 cluster items that sell well, namely Cappucino, Vanilla Coffee Latte, Hazelnut, Taro, Lychee Tea, Japanese, and Greentea, 14 cluster items not selling, namely Americano, Espresso, Moccacino, Kopi tubruk, Vietnam Drip, Sundanese coffee, Avocado Coffee Latte, Match, Strawberry Tea, Strawberry Milkshake, Banana, Coffee Lemon, Kopi Susu, and risol. From the clustering process using the k-means algorithm, the DBI (Davies Bouldin Index) value is obtained with a value of -0,933. These results can be utilized by the Cafe 47°Coffee entrepreneurs to improve their sales strategy and stock management. Key words: K-Means, Data Mining, Clustering, Sales, Cafe Cafe 47°Coffee adalah salah satu cafe yang bergerak dibidang kuliner yang menyediakan makanan dan minuman. Dengan banyaknya pesaing bisnis dibidang cafe maka dari itu pengusaha cafe 47°Coffee diharuskan mampu bersaing dalam menentukan strategi penjualan dengan memanfaatkan data transaksi penjualan. Data yang digunakan pada penelitian ini yaitu data penjualan dari bulan Juli 2021 sampai dengan Februari 2022. Pengusaha cafe 47°Coffee memanfaatkan Data Mining untuk membantu mengambil keputusan strategi penjualan agar dapat mengetahui produk yang harus ditingkatkan dan memberi solusi pengambil keputusan, salah satu metode yang digunakan adalah metode pengelompokan clustering dengan menggunakan algoritma K-Means. Pengusaha Cafe 47°Coffee mengelompokan produk kedalam 3 kriteria yaitu sangat laku, laku, dan tidak laku. Data diolah dengan perhitungan manual dan menggunakan tools Rapid Miner untuk melakukan pengujian, sehingga dapat hasil akhir berupa 4 item cluster sangat laku yakni V60, Caramel Coffee Latte, Red Velvet, dan Coklat , 7 item cluster laku yakni Cappucino, Vanilla Coffee Latte, Hazelnut, Taro, Lychee Tea, Japanese, dan Greentea, 14 item cluster tidak laku yakni Americano, Espresso, Moccacino, Kopi tubruk, Vietnam Drip, Kopi sundan, Avocado Coffee Latte, Match, Strawberry Tea, Milkshake Strawberry, Banana, Coffee Lemon, Kopi susu, dan risol.Dari proses clustering menggunakan algoritma k-means diatas diperoleh nilai DBI (Davies Bouldin Index) dengan nilai -0,933. Hasil ini dapat dimanfaatkan pengusaha Cafe 47°Coffee untuk meningkatkan strategi penjualan dan manajemen stok. Kata kunci: K-Means, Data Mining, Clustering, Penjualan, Cafe

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 034
NIM/NIDN Creators: 41518010096
Uncontrolled Keywords: K-Means, Data Mining, Clustering, Penjualan, Cafe
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.3 Bibliographic Analysis and Control/Bibliografi Analisis dan Kontrol Perpustakaan
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 020 Library and Information Sciences/Perpustakaan dan Ilmu Informasi > 025 Operations, Archives, Information Centers/Operasional Perpustakaan, Arsip dan Pusat Informasi, Pelayanan dan Pengelolaan Perpustakaan > 025.4 Subject Analysis and Control/Subjek Analisis dan Kontrol Perpustakaan
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: LUTHFIAH RAISYA ARDANI
Date Deposited: 15 Sep 2022 10:10
Last Modified: 19 Sep 2022 02:23
URI: http://repository.mercubuana.ac.id/id/eprint/69142

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