ANALISIS PENJUALAN COFFE SHOP KOPIIYA DATA SEMASA SESUDAH PANDEMI DENGAN ALGORITMA APRIORI DAN K-MEANS

RIDWAN, MUHAMAD (2024) ANALISIS PENJUALAN COFFE SHOP KOPIIYA DATA SEMASA SESUDAH PANDEMI DENGAN ALGORITMA APRIORI DAN K-MEANS. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

One form of business that is growing rapidly in the beverage industry is coffee shops. This is motivated by the function of the coffee shop itself, it is not surprising that nowadays, various kinds of coffee shop brands have emerged, for example the kopiiya brand located in Cengkareng district. With the majority of consumers being teenagers, coffee shops are rarely empty of visitors. This is because teenagers generally like to gather with their peers, but since the emergence of the COVID-19 virus pandemic in Indonesia, the Indonesian government has issued PSBB regulations. In this study, clustering and comparison methods during and after the pandemic were used. The data is stored in databases, data warehouses, or other data storage places. Data mining is one part of artificial intelligence. Techniques in data mining are association, and prediction. The data mining techniques used in this research are clustering with the Apriori and K-Means algorithms. The clustering technique does not have a target variable in clustering. Clustering is one of the data mining methods that is directionless, namely hierarchical clustering and non-hierarchical clustering. The resulting rule is easy to communicate, does not require labeled data because it is a complete algorithm, to determine the number of clusters the initial centroid value of the iteration. Knowledge can be data patterns or valid relationships between data. Includes methods that are the intersection of AI, machine learning, and database systems. Analysis calculation process, and data processing. Data exploration using google colab provides a computational narrative, a data that can be added to analysis and decisions. Because the data will be analyzed. Google colab with this tool, aims to analyze business data during and after the pandemic. Clustering is accurate and this business can be surfaiv from during the pandemic. So that if a pandemic comes back there is no need to worry. Keywords: coffee shop, clustering, data mining Salah satu bentuk usaha yang berkembang pesat di industri minuman adalah coffee shop. Hal ini dilatar belakangi oleh fungsi coffee shop itu sendiri, Tidak heran jika saat ini, muncul berbagai macam brand coffee shop, contohnya brand kopiiya yang terletak di kecamatan cengkareng. Dengan mayoritas konsumen adalah remaja menyebabkan coffee shop jarang sepi pengunjung. Hal ini dikarenakan pada umumnya para remaja gemar berkumpul dengan kawan sebaya, Namun sejak munculnya pandemi virus COVID-19 di Indonesia, pemerintah Indonesia mengeluarkan peraturan PSBB. Dalam penelitian ini, Penelitian yang dilakukan metode clustering dan perbandingan semasa dan sesudah pandemi. Data tersebut tersimpan di basis data, gudang data, atau tempat penyimpanan data lainnya. Penambangan data merupakan salah satu bagian dari kecerdasan buatan. Teknik dalam data mining yaitu asosiasi, dan prediksi. Teknik penambangan data yang dipakai dalam penelitian ini yaitu clustering dengan algoritma Apriori dan K-Means. Teknik clustering tidak mempunyai variable target dalam melakukan pengelompokan. Clustering merupakan salah satu metode data mining yang bersifat tanpa arahan, yaitu hierarchical clustering dan non-hierarchical clustering. Aturan yang dihasilkan mudah dikomunikasikan, tidak memerlukan data berlabel karena merupakan algoritmanya lengkap, Untuk menentukan jumlah cluster nilai centroid awal dari iterasi. Pengetahuan dapat berupa pola data atau relasi antar data yang valid. Meliputi metode-metode yang merupakan irisan dari AI, machine learning, dan database system. Proses perhitungan analisis, dan pengolahan data. Eksplorasi data menggunakan google colab memberikan narasi komputasi, sebuah data yang dapat ditambahkan analisis dan keputusan. Karena data tersebut akan dianalisis. Google colab dengan tools ini, bertujuan untuk menganalisis data bisnis semasa dan sesudah pandemi. Clustering yang akurat dan bisnis ini bisa surfaiv dari semasa pandemi. Agar jika terjadi pandemi datang kembali tidak perlu risau. Kata Kunci: coffe shop, clustering, data mining

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 24 113
NIM/NIDN Creators: 41520110005
Uncontrolled Keywords: coffe shop, clustering, data mining
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma
600 Technology/Teknologi > 660 Chemical Engineering and Related Technologies/Teknologi Kimia dan Ilmu yang Berkaitan > 663 Baverege Technology/Teknologi Pembuatan Minuman Komersial > 663.6 Nonalcoholic Beverages/Teknologi Pembuatan Minuman Non Alkohol
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: khalimah
Date Deposited: 31 Jul 2024 02:46
Last Modified: 31 Jul 2024 02:46
URI: http://repository.mercubuana.ac.id/id/eprint/89925

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