ANALISIS DATA PENJUALAN GHUROBA COFFEE MENGGUNAKAN PENDEKATAN DATA MINING

MANIK, RAYVALDO PRAWIRA (2022) ANALISIS DATA PENJUALAN GHUROBA COFFEE MENGGUNAKAN PENDEKATAN DATA MINING. S1 thesis, Universitas Mercu Buana Bekasi.

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Abstract

ABSTRAK Nama : Rayvaldo Prawira Manik NIM : 41518210025 Pembimbing TA : Dr. Ida Nurhaida, S.T., M.T. Judul : ANALISIS DATA PENJUALAN GHUROBA COFFEE MENGGUNAKAN PENDEKATAN DATA MINING Analisis Data penjualan menggunakan pendekatan Data Mining. Data mining adalah proses pengolahan data secara otomatis, Data mining dilakukan untuk mencari pengetahuan tentang pola pembelian komsumen. Dalam mencari pola pembelian konsumen penulis menggunakan beberapa algoritma yaitu Algoritma Apriori, Fp-Growth dan ECLAT, penulis menggunakan algoritma tersebut agar dapat menentukkan hasil pembetunkan pola pembelian konsumen yang cukup akurat. Ketiga algoritma tersebut menggunakan metode Association Rule dalam pencarian pola pembelian konsumen, dengan cara mencari nilai confidence dan support pada setiap produk. Nilai confindence dan support tersebut digunakan sebagai pembentuk pola pembelian konsumen, setelah pola pembelian konsumen telah ditemukan data tersebut dapat digunakan sebagai acuan pemilik kedai kopi dalam melakukan promosi atau strategi pemasaran berdasarkan data penjualan yang sudah diolah tersebut, sehingga data penjualan yang terdapat di Ghuroba Coffee dapat digunakan dan tidak terbuang begitu saja. Kata kunci: Data mining, Algoritma Apriori, Associtaion Rules, Algoritma Eclat, Algoritma Fp-Growth ABSTRACT Name : Rayvaldo Prawira Manik Student Number : 41518210025 Counsellor : Dr. Ida Nurhaida, S.T., M.T. Title : ANALYSIS OF GHUROBA COFFEE SALES DATA USING A DATA MINING APPROACH Sales data analysis uses a Data Mining approach. Data mining is an automatic data processing process. Data mining is done to seek knowledge about consumer purchasing patterns. In looking for consumer buying patterns, the writer uses several algorithms, namely the Apriori Algorithm, Fp-Growth and ECLAT, the author uses these algorithms in order to be able to determine the results of making consumer buying patterns that are quite accurate. The three algorithms use the Association Rule method in searching for consumer buying patterns, by finding the value of confidence and support for each product. The value of confidence and support is used as a shaper of consumer purchasing patterns, after consumer purchasing patterns have been found, the data can be used as a reference for coffee shop owners in carrying out promotions or marketing strategies based on the processed sales data, so that the sales data contained in Ghuroba Coffee can be used as a reference. used and not wasted. Key words: Data mining, Apriori Algorithm, Association Rules, Eclat Algorithm, Fp-Growth Algorithm

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO 22 030
NIM/NIDN Creators:	41518210025
Uncontrolled Keywords:	Kata kunci: Data mining, Algoritma Apriori, Associtaion Rules, Algoritma Eclat, Algoritma Fp-Growth
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 > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data > 005.5 General Purpose Application Programs/Program Aplikasi dengan Kegunaan Khusus
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	siti maisyaroh
Date Deposited:	19 Dec 2022 04:36
Last Modified:	19 Dec 2022 04:36
URI:	http://repository.mercubuana.ac.id/id/eprint/72601

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