PENERAPAN ALGORITMA FREQUENT PATTERN GROWTH UNTUK MELAKUKAN BUNDLING HARGA PADA APLIKASI WEBSITE

MAULANA, ALIFFIO SYAH (2024) PENERAPAN ALGORITMA FREQUENT PATTERN GROWTH UNTUK MELAKUKAN BUNDLING HARGA PADA APLIKASI WEBSITE. S1 thesis, Universitas Mercu Buana Jakarta.

[img] Text (HAL COVER)
01 COVER.pdf

Download (450kB)
[img] Text (ABSTRAK)
02 ABSTRAK.pdf
Restricted to Registered users only

Download (136kB)
[img] Text (BAB I)
03 BAB 1.pdf
Restricted to Registered users only

Download (170kB)
[img] Text (BAB II)
04 BAB 2.pdf
Restricted to Registered users only

Download (306kB)
[img] Text (BAB III)
05 BAB 3.pdf
Restricted to Registered users only

Download (205kB)
[img] Text (BAB IV)
06 BAB 4.pdf
Restricted to Registered users only

Download (1MB)
[img] Text (BAB V)
07 BAB 5.pdf
Restricted to Registered users only

Download (124kB)
[img] Text (DAFTAR PUSTAKA)
08 DAFTAR PUSTAKA.pdf
Restricted to Registered users only

Download (153kB)
[img] Text (LAMPIRAN)
09 LAMPIRAN.pdf
Restricted to Registered users only

Download (3MB)

Abstract

This research aims to create an association method or combination of a relationship on sales products in order to create a combination product or commonly referred to as bundling products using the FP-Growth algorithm with the implementation of web-based results. By utilizing transaction data that has been made from sample data obtained from kaggle, this research can produce several association rules on fp-growth calculations that have been made previously by applying the fp-tree generation model, conditional pattern base generation, conditional fp-tree generation, and frequent itemset search with a minimum support count value of 30% and a minimum confidence value of 50% resulting in 24 rules that are in accordance with the conditions of a total of 32 rules which include if you buy product 2 then there is a possibility of buying product 1 with a support value of 30% and a confidence value of 100%, if you buy product 7 then there is a possibility of buying product 3 with a support value of 30% and a confidence value of 60%, and if you buy product 7 then there is a possibility of buying products 3 and 5 with a support value of 30% and a confidence value of 60%. Kata Kunci : Data Mining, fp-growth, association, ecommerce Penilitian ini bertujuan untuk membuat sebuah metode asosiasi atau kombinasi dari sebuah hubungan pada produk penjualan guna untuk membuat produk kombinasi atau yang biasa disebut dengan bundling product dengan menggunakan algoritma FP-Growth dengan impelementasi hasil berbasis web. Dengan memanfaatkan data transaksi yang sudah dibuat dari data sampel yang didapatkan dari kaggle, penelitian ini dapat menghasilkan beberapa aturan asosiasi pada perhitungan fp-growth yang telah dibuat sebelumnya dengan menerapkan model pembuatan fp-tree, pembangkitan conditional pattern base, pembangkitan conditional fp-tree, dan pencarian frequent itemset dengan nilai minimum support count 30% dan nilai minimum confidence 50% menghasilkan 24 aturan yang sudah sesuai dengan kondisi dari total 32 aturan yang diantaranya adalah jika membeli produk 2 maka akan ada kemungkinan membeli produk 1 dengan nilai support sebesar 30% dan nilai confidence sebesar 100%, jika membeli produk 7 maka akan ada kemungkinan membeli produk 3 dengan nilai support sebesar 30% dan nilai confidence sebesar 60%, dan jika membeli produk 7 maka akan ada kemungkinan membeli produk 3 dan 5 dengan nilai support sebesar 30% dan nilai confidence sebesar 60%. Kata Kunci : Data Mining, fp-growth, asosiasi, ecommerce

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 24 056
Call Number: SIK/15/24/046
NIM/NIDN Creators: 41519120065
Uncontrolled Keywords: Data Mining, fp-growth, asosiasi, ecommerce
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
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
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 > 006 Special Computer Methods/Metode Komputer Tertentu > 006.4 Computer Pattern Recognition/Pola Pengenalan Komputer
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 > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data] > 658.05 Data Processing Computer Applications/Pengolahan Data Aplikasi Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: khalimah
Date Deposited: 27 Feb 2024 06:49
Last Modified: 27 Feb 2024 06:49
URI: http://repository.mercubuana.ac.id/id/eprint/86598

Actions (login required)

View Item View Item