scholarly journals Assosiation Rules for Product Sales Data Analysis Using The Apriori Algorithm

SinkrOn ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 84
Author(s):  
Jarseno Pamungkas ◽  
Yopi Handrianto
Keyword(s):  
A Priori ◽  
Data Mining Algorithm ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Sales Strategy ◽  
Sales Process ◽  
Calculation Process ◽  
Product Sales ◽  
The Relationship ◽  
A Company

To increase sales transactions, the company must be able to compete with other competitors so that it requires an appropriate strategy in carrying out the sales process carried out. In addition to the marketing strategy, the company must be able to analyze the products sold based on the number of sales that have occurred so that the company can see which products are more dominant in consumer demand so that the company can determine a more effective sales strategy. PT. Surya Indah City is a company engaged in the sale of various clothing and accessories. In an effort to increase sales of its products, an analysis is needed to be able to increase company revenue by utilizing sales transaction data it has. To analyze the relationship between clothing products and accessories which are more predominantly sold and other available clothing and accessories products, a data mining algorithm is used, namely the a priori algorithm. With the help of the tanagra application to carry out the calculation process, the dominant product that consumers are interested in can be determined. By using two variables that meet support and minimum confidence, it can be concluded that the most sold products are from the type of clothing, namely clothes and pants. It was concluded that the results of the known final association rules, if you buy a shirt, you will buy pants with 50% support and 75% confidence. If you buy pants, you will buy clothes with 50% support and 85% confidence.

scholarly journals Implementation of Apriori Algorithm Data Mining for Increase Sales

SinkrOn ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Reza Alfianzah ◽  
Rani Irma Handayani ◽  
Murniyati Murniyati
Keyword(s):  
Data Mining ◽  
Business Strategy ◽  
A Priori ◽  
Data Mining Algorithm ◽  
Sales Data ◽  
The Right ◽  
Or Organization ◽  
Product Sales ◽  
The Relationship ◽  
Confidence Value

Any company or organization that wants to survive needs to determine the right business strategy. The product sales data carried out by Lakoe Dessert Pondok Kacang will eventually result in a pile of data, so it is unfortunate if it is not re-analyzed. The products offered vary with a wide variety of products as many as 45 products, to find out the products with the most sales and the relationship between one product and another, one of the algorithms is needed in the data mining algorithm, namely the a priori algorithm to find out, and with the help of the Rapidminer 5 application, with a support value 2,4% and a confidence value 50%, products that customers often buy or are interested in can be found. This study used sales data for March 2020, which amounted to 209 transaction data. From the research, it was found that the item with the name Pudding Strawberry and Pudding Vanilla was the product most purchased by consumers. With knowledge of the most sold products and the patterns of purchasing goods by consumers, Lakoe Dessert Pondok Kacang can develop marketing strategies to market other products by analyzing the profits from selling the most sold products and anticipating running out or empty of stock or materials at a later date.

scholarly journals APPLICATION OF DATA MINING TO DETERMINE PRODUCT ADMINISTRATION USING APRIORI ALGORITHM

2019 ◽  
Vol 4 (1) ◽  
pp. 18-32
Author(s):  
Zunita Wulansari
Keyword(s):  
Data Mining ◽  
A Priori ◽  
Apriori Algorithm ◽  
Sales Data ◽  
Sales Strategy ◽  
A Company

Product Arrangement is a way of arranging products to attract consumers. Product arrangement is also known as display. But in fact there are still many entrepreneurs who have not paid attention to the arrangement of their products. So that many consumers are not interested in buying products because the arrangement is less attractive which makes the company's income does not increase. Therefore researchers have a solution to solve the problems that exist in the shop. That is, with the application of data mining to determine the arrangement of products using a priori algorithm, the results can be used as a company guide to determine the display of goods and as a guide to promote goods that are less sold to participate or sell quickly. Based on the results of the trials that have been carried out, it is known that the a priori algorithm is used to help determine the product structuring solution from the sales data of Warung Sayur Segar products so that it can later be used as a consideration in determining an effective structuring and sales strategy.

Market Basket Analysis with Apriori Algorithm and Frequent Pattern Growth (Fp-Growth) on Outdoor Product Sales Data

2021 ◽  
Vol 2 (1) ◽  
pp. 132-139
Author(s):  
Wiwit Pura Nurmayanti ◽  
Hanipar Mahyulis Sastriana ◽  
Abdul Rahim ◽  
Muhammad Gazali ◽  
Ristu Haiban Hirzi ◽  
...  
Keyword(s):  
Association Rules ◽  
Association Rule ◽  
Frequent Pattern ◽  
Apriori Algorithm ◽  
Market Basket Analysis ◽  
Market Basket ◽  
Transaction Data ◽  
Pattern Growth ◽  
Product Sales ◽  
The Relationship

Indonesia is an equatorial country that has abundant natural wealth from the seabed to the top of the mountains, the beauty of the country of Indonesia also lies in the mountains that it has in various provinces, for example in the province of West Nusa Tenggara known for its beautiful mountain, namely Rinjani. The increase in outdoor activities has attracted many people to open outdoor shops in the West Nusa Tenggara region. Sales transaction data in outdoor stores can be processed into information that can be profitable for the store itself. Using a market basket analysis method to see the association (rules) between a number of sales attributes. The purpose of this study is to determine the pattern of relationships in the transactions that occur. The data used is the transaction data of outdoor goods. The analysis used is the Association Rules with the Apriori algorithm and the frequent pattern growth (FP-growth) algorithm. The results of this study are formed 10 rules in the Apriori algorithm and 4 rules in the FP-Growth algorithm. The relationship pattern or association rule that is formed is in the item "if a consumer buys a portable stove, it is possible that portable gas will also be purchased" at the strength level of the rules with a minimum support of 0.296 and confidence 0.774 at Apriori and 0.296 and 0.750 at FP-Growth.  

scholarly journals Analysis of Customer Transaction Data Associations Based on The Apriori Algorithm

2020 ◽  
Vol 3 (1) ◽  
pp. 23-28
Author(s):  
Tri Astuti ◽  
Bella Puspita
Keyword(s):  
Data Mining ◽  
Building Materials ◽  
Main Product ◽  
Small And Medium Enterprises ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Sales Strategy ◽  
Data Mining Approach ◽  
Sales Process ◽  
Medium Enterprises

UD Dian Pertiwi is one of the small and medium enterprises engaged in materials with the main product is building materials. This business experiences large amounts of transactions every day, the data obtained becomes increasingly large, and it will only be limited to a pile of useless data or commonly called junk. By utilizing a data mining approach apriori algorithm technique, the data can be utilized to support the sales process and achieve a target of UD Dian Pertiwi. Based on research and data mining that has been done using association analysis and apriori algorithms by applying a minimum of support = 1% and a minimum of confidence = 70% resulted in the ten strongest association rules can be used by UD Dian Pertiwi in the process of applying a sales strategy including determining interrelationships, in short, the product has the potential to be purchased at the same time, increasing the amount of product stock and conducting promotions.

scholarly journals IMPLEMENTASI METODE DATA MINING APRIORI PADA APLIKASI PENJUALAN PT. TIGA RAKSA SATRIA

2020 ◽  
Vol 17 (1) ◽  
pp. 329-338
Author(s):  
Siti Qomariah ◽  
Hanifah Ekawati ◽  
Sepriyadi Belareq
Keyword(s):  
Data Mining ◽  
A Priori ◽  
Apriori Algorithm ◽  
Analysis Method ◽  
Strategic Information ◽  
Sales Data ◽  
Data Application ◽  
Recording Process ◽  
Product Sales ◽  
A Company

PT. Tiga Raksa Satria, Tbk is a company engaged in trading in the form of selling products of various brands to shops in Samarinda. the recording process of selling has been done computerized, but the sales data has not been processed optimally. there is no application that analyzes sales data for category, planning and service to consumers. Analyzing sales data is an important part of the company, an analysis of sales results has an impact on the profits to be gained by the company. Datamining is the science of digging up valuable information and knowledge in databases. One algorithm in data mining is a priori algorithm. Datamining is widely implemented in various fields such as business, commerce, and others. This research aims to make an application with the Application of Data Mining Basketball Analysis Method with Apriori Algorithm to process the sales data in a more structured, detailed and know the problems in product sales. This application generates rules that help draw conclusions needed for drawing conclusions of strategic information for companies regarding sales data. Application made with the application of a priori methods helps in the analysis of sales data that is owned.

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

scholarly journals Consumer Customs Analysis Using the Association Rule and Apriori Algorithm for Determining Sales Strategies in Retail Central

2019 ◽  
Vol 125 ◽  
pp. 23003
Author(s):  
Ahmad Heru Mujianto ◽  
Chamdan Mashuri ◽  
Anita Andriani ◽  
Febriana Dwi Jayanti
Keyword(s):  
Association Rule ◽  
Apriori Algorithm ◽  
Average Percentage ◽  
Sales Process ◽  
Rule Method ◽  
Consumer Habits ◽  
A Company ◽  
Sales Strategies

The sustainability of a company will not be separated from the role of consumers in conducting transactions. In fact, a consumer has different behaviour and character, therefore as a company owner must be able to analyze the patterns or habits of consumers in making transactions. This also happens in the retail center X, which has problems in the sales process, such as products running out of stock and unsold products and the most popular products and products that are not in demand by consumers. Therefore we need an analysis of consumer habits in conducting transactions. The method of association rule with Apriori algorithm is able to be applied well in the analysis of the habits of consumer transactions in the central retail X. The results of the calculation obtained an average percentage of the value of support 33%-40% and the value of confidence 43%-80%. The results of applying the association rule method with Apriori algorithm can help recommend central retail X owners in structuring product and determine strategic steps in increasing sales, such as providing discounts or promos for certain products.

scholarly journals APPLICATION OF DATA MINING FOR ANALYSIS OF CONSUMER PURCHASE DATA ON SALES TRANSACTION DATA AT HALAL MART HNI HPAI DHARMASRAYA

2020 ◽  
Vol 3 (1) ◽  
pp. 68-75
Author(s):  
Sri Kurnia Yuliarnis ◽  
Yeka Hendriyani ◽  
Denny Kurniadi ◽  
M. Giatman
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Online Media ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Sales Strategy ◽  
Using Data ◽  
Purchase Patterns ◽  
Product Layout ◽  
Archive Data

The sales strategy determines the continuity of the business being run. The problems that occur are the sales archive data has not been analyzed in-depth, the information system has not been integrated with applications for sales data analysis, online media promotion has not been maximized, inadequate stock of goods, the layout of goods is not optimal, and the combination of the number of products is not optimal. This study aims to extract hidden information in the sales database using Data Mining. From the information generated, sales strategy recommendations are developed relating to promotions, inventory, catalogue design, item layout, and the combination of product quantities. The method used is the association rule with Apriori algorithm to find consumer purchase patterns through the resulting association. The importance of association can be identified by two benchmarks, namely support and confidence. The sales strategy analyzed includes product promotion, catalogue design, product layout, stock predictions, and product combinations for sale. Based on the research produced 7 strong rules which are the highest association rules which are then developed into a sales strategy recommendation.

IMPLEMENTASI METODE DATA MINING APRIORI PADA APLIKASI PENJUALAN PT. TIGA RAKSA SATRIA

2020 ◽  
Vol 17 (1) ◽  
pp. 329-338
Author(s):  
Siti Qomariah ◽  
Hanifah Ekawati ◽  
Sepriyadi Belareq
Keyword(s):  
Data Mining ◽  
A Priori ◽  
Apriori Algorithm ◽  
Analysis Method ◽  
Strategic Information ◽  
Sales Data ◽  
Data Application ◽  
Product Sales

been done computerized, but the sales data has not been processed optimally. there is no application that analyzes sales data for category, planning and service to consumers. Analyzing sales data is an important part of the company, an analysis of sales results has an impact on the profits to be gained by the company. Datamining is the science of digging up valuable information and knowledge in databases. One algorithm in data mining is a priori algorithm. Datamining is widely implemented in various fields such as business, commerce, and others. This research aims to make an application with the Application of Data Mining Basketball Analysis Method with Apriori Algorithm to process the sales data in a more structured, detailed and know the problems in product sales. This application generates rules that help draw conclusions needed for drawing conclusions of strategic information for companies regarding sales data. Application made with the application of a priori methods helps in the analysis of sales data that is owned. 

Rancang Bangun Inventarisasi Barang menggunakan Algoritma Apriori Sebagai Data Mining

2021 ◽  
Vol 5 (4) ◽  
pp. 354
Author(s):  
Aditya Prasetya ◽  
Septi Andriana ◽  
Ratih Titi Komalasari
Keyword(s):  
Data Mining ◽  
Programming Language ◽  
A Priori ◽  
Apriori Algorithm ◽  
Transaction Data ◽  
Important Thing ◽  
Minimum Support ◽  
Manual Method ◽  
The Times ◽  
Modern Era

Inventory activities become an important thing for business progress, along with the times, inventory activities become easier due to the large number of facilities and infrastructure to support activities, including the Ap Jaya Store which also competes in the modern era, but currently, inventory activities in stores Ap Jaya still uses the manual method, namely by recording inventory activities using a book then recapitulating one by one so that it takes a lot of time, along with these problems an inventory application is needed that can be used to support these activities, this inventory application is made using the a priori algorithm method as data mining and using the programming language PHP and MySQL as a database besides that the a priori algorithm can also be used for item recommendation systems, on testing with 20 transaction data with a minimum support value = 20% and a minimum confidence = 70% also from the results of the transaction. Tests carried out using the apriori algorithm and using applications that are made get the same results according to the requirements for support and confidence values.Keywords:Inventory, Data Mining, Apriori Algorithm

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