scholarly journals Penerapan Data Mining Untuk Analisis Daftar Pembelian Konsumen Dengan Menggunakan Algoritma Apriori Pada Transaksi Penjualan Toko Bangunan MDN

2021 ◽  
Vol 2 (2) ◽  
pp. 89-101
Author(s):  
Edo Tachi Naldy ◽  
Andri Andri
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Building Material ◽  
Apriori Algorithm ◽  
Processing Methods ◽  
Data Reporting ◽  
Transaction Data ◽  
Minimum Support ◽  
Minimum Value

Everyday the MDN Building Shop has sales transactions but these transactions are only used as data reporting, MDN Building Stores do not manage sales transaction data and analyze a relationship between building material products purchased by consumers in the future. The purpose of this study is to process sales transaction data from consumer purchases by utilizing the Apriori Algorithm, one of the data mining processing methods. From the Apriori algorithm that will be used, it will find an association rule by finding the minimum value of support and confidence. The final result is that if the minimum support value is 50% and the minimum trust is 90%, then 10 patterns of consumer purchase transactions are obtained with 100% confidence. From the association rules, it was found that the transactions that occurred were the purchase of Knie In Grest, Tee in grest, gelam 10 x 12, thinner bottles, knie grest 3 in, waving aw pipes, speck gloves, 3 mm polywood, and 1 nail in a keris.

scholarly journals IMPLEMENTASI METODE MARKET BASKET ANALYSIS (MBA) MENGGUNAKAN ALGORITMA APRIORI DALAM TRANSAKSI PENJUALAN (STUDI KASUS: KAFE RUANG TEMU)

2020 ◽  
Vol 10 (2) ◽  
pp. 138
Author(s):  
Muhammad SyahruRomadhon ◽  
Achmad Kodar
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Apriori Algorithm ◽  
Market Basket Analysis ◽  
Tourist Attractions ◽  
Market Basket ◽  
Transaction Data ◽  
Data Mining Techniques ◽  
Minimum Support

Jakarta is one of the culinary attractions, many tourist attractions every year become creative in business. One of them is a cafe. Cafe Ruang Temu has sales transaction data but is not used to see associations between one product and another. In this case there needs to be a system for finding menu combinations by processing sales transactions. One of the data mining techniques is association rule or Market Basket Analysis (MBA) with apriori algorithm. Apriori algorithm aims to produce association rules to form menu combinations. The sales dataset for January 2019 to July 2019 is determined by the minimum support and minimum confidence values that have been set.  

scholarly journals Combination, Pola, Apriori ANALISIS POLA BELANJA KONSUMEN MENGGUNAKAN ALGORITMA APRIORI PADA RAFFA PHOTOCOPY

2019 ◽  
Vol 2 (2) ◽  
pp. 63-73
Author(s):  
Nurul Azwanti
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Minimum Support ◽  
Association Pattern ◽  
Using Data ◽  
Confidence Value

Raffa Photocopy is a shop that started its business in 2016. This business not only provides photocopy services, but also provides office stationery and school supplies. Every day there are sales transactions where the recording of goods sold has a relationship between one another, because in recording sometimes consumers do not just buy one item, but two items even more as when buying a book, it is likely that consumers also buy a pen. This recording is only stored as an archive by Raffa Photocopy, even though the number of sales transactions that occur every day can lead to a pile of data. One effort to increase sales at Raffa Photocopy can be done by processing transaction data that overlaps by using data mining association techniques. This association rule technique uses the Apriori algorithm which deals with the study of 'what is with what' or discovers the association pattern of items that are often bought. The results of this study in the form of rules include the first, if you buy an eraser, it is likely that consumers also buy notebooks simultaneously. Second, if you buy Tipex, then consumers also buy a double folio. The results of the Apriori algorithm process are based on a minimum support value of 35% and a minimum confidence value of 80%.

scholarly journals Implementation of Apriori Algorithm for Determining Purchase Patterns in One Transaction

2018 ◽  
Vol 7 (4.33) ◽  
pp. 204
Author(s):  
Murnawan . ◽  
Ardiles Sinaga ◽  
Ucu Nughraha
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Apriori Algorithm ◽  
Market Basket Analysis ◽  
Market Basket ◽  
Transaction Data ◽  
Future Developments ◽  
Operational Activities ◽  
Purchase Patterns

The organization data owned is one of the assets of the organization. With the daily operational activities, the longer the data will increase. By using techniques that can do data processing, these data can be obtained important information that can be used for future developments. Association rules are one of these techniques which aims to find patterns in the form of products that are often purchased together or tend to appear together in a transaction from transaction data which is generally very large by using the concept association rules themselves derived from Market Basket Analysis terminology, namely search for relationships from several products in a purchase transaction. In designing this application will build applications that classify the data items based on the tendency to appear together in a transaction using the Apriori Algorithm. The Apriori algorithm is the first algorithm and is often used to find association rules in data mining applications with association rule techniques. 

scholarly journals The Use of Apriori Algorithm in the Formation of Association Rule at Lotteria Cibubur

SinkrOn ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 76
Author(s):  
Ovi Liansyah ◽  
Henny Destiana
Keyword(s):  
Data Mining ◽  
Data Storage ◽  
Association Rules ◽  
Association Rule ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Data Mining Techniques ◽  
Sales Data ◽  
Sales Strategy ◽  
Data Mining Application

Lotteria as one of the franchises that produce sales data every day, has not been able to maximize the utilization of that data. The sale data storage is still not optimal. By utilizing sales transaction data that have been stored in the database, the management can find out the menus purchased simultaneously, using the association rule. Namely, data mining techniques to find the association rules of a combination of items. The process of searching for associations uses the help of apriori algorithms to produce patterns of the combination of items and rules as important knowledge and information from sales transaction data. By using the minimum support parameters, the minimum and the month period of the sales transaction to find the association rules, the data mining application generates association rules between items in April 2019, where consumers who buy hot / ice coffee will then buy float together with support of 16% and 100% confidence. Knowing which menu products or items are the most sold, thus lotteria Cibubur can develop a sales strategy to sell other types of menu products by examining the advantages of the most sold menu with other menus and can increase the stock of menu ingredients.

scholarly journals Analisa Data Mining Terhadap Penjualan Food Dengan Metode Apriori Pada Kopsyahira

2020 ◽  
Vol 8 (1) ◽  
pp. 44-48
Author(s):  
Agung Riyanto ◽  
Melan Susanti
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Limiting Factor ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Minimum Support ◽  
To Come ◽  
Food Sales

Every company engaged in trade must have a strategy to improve service. Some of them regulate the arrangement of goods (display) or make the appearance of a store look attractive and make shopping easier so that consumers are willing to come back to shop. Many transactions every day but are still done manually. So there might be a lot of errors and inaccurate reports. The number of transactions is also only used as a document. It is not possible for many transaction data to be lost or tucked away. Collection of transaction data if left alone for months, then the data will only be meaningless data and will be a limiting factor in improving services. Purchases are often done simultaneously at one time, so there is a queue in the store. In Kopsyahira there were also several obstacles in terms of sales, especially food sales. In this study, researchers will use the Apriori algorithm, the author uses Tanagra's data mining software. The results of this study produce 2 final association rules if using a minimum support of 30% and Confidence of 66%.

scholarly journals IMPLEMENTASI ALGORITMA APRIORI TERHADAP DATA PENJUALAN PADA PERUSAHAAN RETAIL

2019 ◽  
Vol 15 (1) ◽  
pp. 85-90 ◽  
Author(s):  
Jordy Lasmana Putra ◽  
Mugi Raharjo ◽  
Tommi Alfian Armawan Sandi ◽  
Ridwan Ridwan ◽  
Rizal Prasetyo
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Apriori Algorithm ◽  
Business World ◽  
Transaction Data ◽  
Retail Company ◽  
Special Strategy

The development of the business world is increasingly rapid, so it needs a special strategy to increase the turnover of the company, in this case the retail company. In increasing the company's turnover can be done using the Data Mining process, one of which is using apriori algorithm. With a priori algorithm can be found association rules which can later be used as patterns of purchasing goods by consumers, this study uses a repository of 209 records consisting of 23 transactions and 164 attributes. From the results of this study, the goods with the name CREAM CUPID HEART COAT HANGER are the products most often purchased by consumers. By knowing the pattern of purchasing goods by consumers, the company management can increase the company's turnover by referring to the results of processing sales transaction data using a priori algorithm

Research of Association Rules Algorithm Based on Matrix under Cloud Computing

2014 ◽  
Vol 568-570 ◽  
pp. 798-801
Author(s):  
Ye Qing Xiong ◽  
Shu Dong Zhang
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Association Rules ◽  
Apriori Algorithm ◽  
Computing Technology ◽  
Binary Matrix ◽  
Transaction Data ◽  
Big Data Mining ◽  
Parallel Mining

It occurs time and space performance bottlenecks when traditional association rules algorithms are used to big data mining. This paper proposes a parallel algorithm based on matrix under cloud computing to improve Apriori algorithm. The algorithm uses binary matrix to store transaction data, uses matrix "and" operation to replace the connection between itemsets and combines cloud computing technology to implement the parallel mining for frequent itemsets. Under different conditions, the simulation shows it improves the efficiency, solves the performance bottleneck problem and can be widely used in big data mining with strong scalability and stability.

The Application of Apriori Algorithm in Analysis on Admitted Students of Colleges and Universities

2013 ◽  
Vol 321-324 ◽  
pp. 2578-2582
Author(s):  
Qian Zhang
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Colleges And Universities ◽  
Apriori Algorithm ◽  
Data Mining Techniques ◽  
Minimum Support ◽  
Sample Data ◽  
Mining Association Rules

This paper examined the application of Apriori algorithm in extracting association rules in data mining by sample data on student enrollments. It studied the data mining techniques for extraction of association rules, analyzed the correlation between specialties and characteristics of admitted students, and evaluated the algorithm for mining association rules, in which the minimum support was 30% and the minimum confidence was 40%.

scholarly journals Implementasi Data Mining Menggunakan Algoritma Apriori Pada Penjualan Suku Cadang Motor

2021 ◽  
Vol 14 (2) ◽  
pp. 125
Author(s):  
Ainul Mardiaha ◽  
Yulia Yulia
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
A Priori ◽  
Spare Parts ◽  
Frequent Itemset ◽  
Sales Data ◽  
Minimum Support ◽  
Relationship Of

This research was carried out to simplify or assist Candra Motor workshop owners in managing data and archives of motorcycle parts sales by applying a data mining a priori algorithm method. Data mining is an operation that uses a particular technique or method to look for different patterns or shapes in a selected data. Sales data for a year with the number of 15 items selected using the priori algorithm method. A priori algorithm is an algorithm for taking data with associative rules (association rule) to determine the associative relationship of an item combination. In a priori algorithm, it is determined frequent itemset-1, frequent itemset-2, and frequent itemset-3 so that the association rules can be obtained from previously selected data. To obtain the frequent itemset, each selected data must meet the minimum support and minimum confidence requirements. In this study using minimum support ? 7 or 0.583 and minimum confidence of 90%. So that some rules of association were obtained, where the calculation of the search for association rules manually and using WEKA software obtained the same results.By fulfilling the minimum support and minimum confidence requirements, the most sold spare parts are inner tube, Yamaha oil and MPX oil.

scholarly journals Implementasi Algoritma Apriori Pada Penyusunan Menu Makanan Rumah Makan Prasmanan

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Asep Budiman Kusdinar ◽  
Daris Riyadi ◽  
Asriyanik Asriyanik
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
High Frequency ◽  
A Priori ◽  
Apriori Algorithm ◽  
Frequency Pattern ◽  
Data Mining Techniques ◽  
Rule Method

A buffet restaurant is a restaurant that provides buffet food that is served directly at the dining table so that customers can order more food according to their needs. This study uses the association rule method which is one of the methods of data mining and a priori algorithms. Data mining is the process of discovering patterns or rules in data, in which the process must be automatic or semi-automatic. Association rules are one of the techniques of data mining that is used to look for relationships between items in a dataset. While  the apriori algorithm is a very well-known algorithm for finding high-frequency patterns, this a priori algorithm is a type of association rule in data mining. High- frequency patterns are patterns of items in the database that have frequencies or support. This high-frequency pattern is used to develop rules and also some other data mining techniques. The composition of the food menu in the Asgar restaurant is now arranged randomly without being prepared on the food menu between one another. The result of this research is  to support the composition of the food menu at the Asgar restaurant so that it is easier to take food menu with one another.  

Sign in / Sign up

Export Citation Format

Share Document