NURHIKMA, NURHIKMA (2024) IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS DATA PENJUALAN (STUDI KASUS: ALFAMART CAMPALAGIAN POLEWALI MANDAR). Diploma thesis, Universitas Sulawesi Barat.
![[thumbnail of NURHIKMA SKRIPSI PENELITIAN S1(BARNING).pdf]](https://repository.unsulbar.ac.id/style/images/fileicons/text.png)
NURHIKMA SKRIPSI PENELITIAN S1(BARNING).pdf
Restricted to Repository staff only
Download (1MB)
![[thumbnail of NURHIKMA SKRIPSI PENELITIAN S1(BARNING)_organized.pdf]](https://repository.unsulbar.ac.id/style/images/fileicons/text.png)
NURHIKMA SKRIPSI PENELITIAN S1(BARNING)_organized.pdf
Download (632kB)
Abstract
Banyaknya persaingan dalam dunia bisnis khususnya pada usaha minimarket, menuntut para pengembang untuk menemukan suatu strategi yang dapat meningkatkan pemesanan produk pada perusahaannya. Setiap perusahaan harus mampu bersaing dan memikirkan bagaimana mereka dapat terus tumbuh dan mengembangkan usaha tersebut. Salah satu cara yang dapat dilakukan yaitu dengan menggunakan data transaksi penjualan yang dimiliki perusahaan. Penelitian ini dilakukan pada minimarket Alfamart Campalagian Polewali Mandar. Penelitian ini bertujuan untuk mengetahui hasil implementasi algoritma apriori untuk analisis data penjualan, peneliti akan melakukan analisis pada data penjualan Alfamart Campalagian Polewali Mandar menggunakan metode pengolahan data yaitu
Algoritma Apriori. Pengolahan data dilakukan dengan dua cara yaitu secara manual dengan bantuan Microsoft Excel dan dengan bahasa pemrograman Python menggunakan Tools Jupyter Notebook. Dalam penelitian ini data yang digunakan yaitu 200 data transaksi dengan 15 jenis item barang yang meliputi makanan dan minuman. Dari hasil penelitian yang dilakukan dengan menerapkan nilai minimum support 10% dan minimum confidence 50% ditemukan pola transaksi pembelian sebanyak 3 aturan asosiasi yaitu Jika membeli Cimory maka membeli Aqua Air
dengan nilai support 13%, nilai confidence 53,06% dengan lift ratio 1,07, Jika membeli Kanzler maka membeli Aqua Air dengan nilai support 12%, nilai confidence 57,14% dengan lift ratio 1,15 dan Jika membeli You C1000 maka membeli Aqua Air dengan nilai support 15%, nilai confidence 60% dengan lift ratio 1,21.
The large amount of competition in the business world, especially in the minimarket business, requires developers to find a strategy that can increase product orders at their company. Every company must be able to compete and think about how they can continue to grow and develop their business. One way that can be done is by using sales transaction data owned by the company. This research was conducted at the Alfamart Campalagian Polewali Mandar minimarket. This research aims to determine the results of implementing the a priori algorithm for sales data analysis. The researcher will carry out analysis on the sales data of Alfamart Campalagian Polewali Mandar using the data processing method, namely the Apriori Algorithm. Data processing was carried out in two ways, namely manually with the help of Microsoft Excel and with the Python programming language using the Jupyter Notebook Tools. In this research, the data used was 200 transaction data with 15 types of goods including food and drinks. From the results of research conducted by applying a minimum support value of 10% and a minimum confidence value of 50%, it was found that there were 3 association rules in purchasing transaction patterns, namely, if you buy Cimory then buy Aqua Air with a support value of 13%, a confidence value of 53.06% with a lift ratio of 1, 07, If you buy Kanzler then buy Aqua Air with a support value of 12%, confidence value 57.14% with a lift ratio of 1.15 and if you buy You C1000 then buy Aqua Air
with a support value of 15%, confidence value 60% with a lift ratio of 1 .21.
Item Type: | Thesis (Diploma) |
---|---|
Additional Information: | IMPLEMENTASI ALGORITMA APRIORI UNTUK ANALISIS DATA PENJUALAN (STUDI KASUS: ALFAMART CAMPALAGIAN POLEWALI MANDAR) |
Uncontrolled Keywords: | Alfamart, Algoritma Apriori, Bahasa Pemrograman Python, Aturan Asosiasi |
Subjects: | FAKULTAS TEKNIK > Informatika |
Divisions: | Fakultas Teknik |
Depositing User: | Unnamed user with email Nurhasyim@gmail.com |
Date Deposited: | 12 Mar 2025 05:49 |
Last Modified: | 12 Mar 2025 05:49 |
URI: | https://repository.unsulbar.ac.id/id/eprint/1527 |