scholarly journals IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI

2020 ◽  
Vol 17 (2) ◽  
pp. 396-402
Author(s):  
Nadya Febrianny Ulfha ◽  
Ruhul Amin
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Marketing Strategies ◽  
Business World ◽  
Association Pattern ◽  
Green Lake ◽  
Purchasing Patterns ◽  
The Relationship ◽  
Confidence Value

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.

scholarly journals IMPLEMENTASI DATA MINING UNTUK MENGETAHUI POLA PEMBELIAN OBAT MENGGUNAKAN ALGORITMA APRIORI

2020 ◽  
Vol 17 (2) ◽  
pp. 396-402
Author(s):  
Nadya Febrianny Ulfha ◽  
Ruhul Amin
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Marketing Strategies ◽  
Business World ◽  
Association Pattern ◽  
Green Lake ◽  
Purchasing Patterns ◽  
The Relationship ◽  
Confidence Value

Competition in the business world requires entrepreneurs to think of finding a way or method to increase the transaction of goods sold. The purpose of this research is to provide drug stock data that is widely purchased by pharmacy customers at Kimia Farma, Green Lake branch in Jakarta. The algorithm used in this study is a priori to determine the relationship between the frequency of sales of drug brands most frequently purchased by customers. The association pattern formed with a minimum support of 40% and a minimum value of 70% confidence produces 17 association rules. The strong rules obtained are that if you buy a 500Mg Ponstan KPL @ 100, you will buy an Incidal OD 10Mg Cap with a support value of 59% and a confidence value of 84%. A priori algorithm can be used by companies to develop marketing strategies in marketing products by examining consumer purchasing patterns.  

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 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 Penerapan Metode Data Mining Pada Point of Sale Berbasis Web Menggunakan Algoritma Apriori

2021 ◽  
Vol 5 (3) ◽  
pp. 1158
Author(s):  
Adam Firmansyah ◽  
M Iwan Wahyudin ◽  
Ben Rahman
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
A Priori ◽  
Point Of Sale ◽  
Minimum Support ◽  
Confidence Value

To be able to understand which products have been purchased by customers, it is done by describing the habits when customers buy. Use association rules to detect items purchased at the same time. This study uses an a priori algorithm to determine the association rules when buying goods. The results of the study and analyzing the data obtained a statement that using the a priori algorithm to select the combined itemset using a minimum support of 25% and a minimum confidence of 100%, found the association rule, namely, if the customer buys at the same time. Buying goods has the highest value of support and trust. Likewise with the support value of 25%, the confidence value is 100%. In this way, if a customer buys an item, the probability that the customer buys the item is 100%

scholarly journals Analisa Association Rule Pada Algoritma Apriori Untuk Minat Pembelian Alat Kesehatan

2021 ◽  
Vol 5 (1) ◽  
pp. 280
Author(s):  
Andi Rahmadsyah ◽  
Hartono Hartono ◽  
Rika Rosnelly
Keyword(s):  
Data Mining ◽  
Medical Devices ◽  
Association Rule ◽  
A Priori ◽  
Mining Method ◽  
Market Basket Analysis ◽  
Business World ◽  
Market Basket ◽  
Analysis Techniques ◽  
The Relationship

In the competition in the business world, especially the Medical Device industry, it requires developers to find an accurate strategy that can increase sales of goods. One way to overcome this problem is to continue to provide various types of medical devices in the warehouse. To find out what medical devices are purchased by consumers, market basket analysis techniques are carried out, namely analysis of consumer buying habits. In order to make it easier for companies to determine Buyers' interest in medical devices, a data mining method is needed which is accompanied by an a priori algorithm based on the purchasing process carried out by consumers based on the relationship between the products purchased. Based on the sample sales data for medical devices CV Andira Karya Jaya, amounting to 25 transactions and in this study a minimum support = 12% and a minimum confidence = 70% will be used. In the final stage, the results obtained are medical devices that are in demand by buyers at CV. Andira Karya Jaya, namely 1 M3 oxygen cylinder and 1 M3 troley of oxygen. Based on this data, CV. Andira Karya Jaya can provide supplies of medical devices that are of interest to buyers.

scholarly journals Algoritma Apriori Untuk Penentuan Assosiasi Penjualan Barang

2021 ◽  
Vol 9 (1) ◽  
pp. 7
Author(s):  
Calvin Ivan Wiryawan ◽  
Yustina Retno Wahyu Utami ◽  
Didik Nugroho
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
A Priori ◽  
Basic Needs ◽  
Marketing Strategies ◽  
Apriori Algorithm ◽  
Growing Up ◽  
Minimum Support ◽  
Data Mining Algorithms ◽  
Mining Algorithms

The increasing of selling basic needs make the company has to provide a lot of goods. The data will be growing up with increasing the transaction at Sari Bumi store. All this time, the selling basic needs at Sari Bumi Store unstructured well so that needed an application with produce important information that can decide marketing strategies. In this research, Apriori algorithm is used to determine association rules. This method was chosen because it is one of the classic data mining algorithms to look for patterns of relationships between one or more items in one dataset. A priori algorithms can help companies in developing marketing strategies. The result of this research is combination between 4 item set with a minimum support of 30% and minimum confidence of 60%.Keywords: sale, staple, apriori algorithm

scholarly journals IMPLEMENTASI ALGORITMA APRIORI DALAM MENENTUKAN PERSEDIAAN OBAT

2017 ◽  
Vol 2 (1) ◽  
Author(s):  
Gusti Ahmad Syaripudin ◽  
Edi Faizal
Keyword(s):  
Data Mining ◽  
Programming Language ◽  
Association Rules ◽  
A Priori ◽  
Marketing Strategies ◽  
Apriori Algorithm ◽  
Drug Supply ◽  
Test Results ◽  
Computer Based ◽  
Algorithm Implementation

Computer-based transaction resulting in the accumulation of data in the database of an application. The data can be reprocessed to obtain important information. Data mining can be used to obtain valuable information for management purposes. The technique can be used are the rules of the association. One type of association rules is a priori algorithm. Application of a priori algorithm has been done in the analysis of sales. The research will be applied to the application pharmacies RMC. The programming language used for the algorithm implementation language is Java with Netbeans Platform 7.4 .DBMS used is MySQL. The test results showed a priori algorithm can be used to identify drugs that may be purchased in conjunction with other drugs, as well as showing the drug most widely sold and least by the set of combinations of items. Such recommendations can be used for management in determining drug supply and design marketing strategies quickly, accurately and efficiently.Keywords: java, apriori algorithm, netbeans, MySQL

scholarly journals Data Mining as Support to Knowledge Management in Marketing

2015 ◽  
Vol 6 (2) ◽  
pp. 18-30 ◽  
Author(s):  
Marijana Zekić-Sušac ◽  
Adela Has
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Knowledge Management ◽  
Association Rules ◽  
Marketing Strategies ◽  
Web Based ◽  
Data Mining Techniques ◽  
Data Mining Approach ◽  
Model Generalization ◽  
Retail Managers

Abstract Background: Previous research has shown success of data mining methods in marketing. However, their integration in a knowledge management system is still not investigated enough. Objectives: The purpose of this paper is to suggest an integration of two data mining techniques: neural networks and association rules in marketing modeling that could serve as an input to knowledge management and produce better marketing decisions. Methods/Approach: Association rules and artificial neural networks are combined in a data mining component to discover patterns and customers’ profiles in frequent item purchases. The results of data mining are used in a web-based knowledge management component to trigger ideas for new marketing strategies. The model is tested by an experimental research. Results: The results show that the suggested model could be efficiently used to recognize patterns in shopping behaviour and generate new marketing strategies. Conclusions: The scientific contribution lies in proposing an integrative data mining approach that could present support to knowledge management. The research could be useful to marketing and retail managers in improving the process of their decision making, as well as to researchers in the area of marketing modelling. Future studies should include more samples and other data mining techniques in order to test the model generalization ability.

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 PENERAPAN ALGORITMA APRIORI DALAM MENENTUKAN POLA PEMBELIAN KONSUMEN DI KAFE HIDDEN TOAST AND FLOAT

2019 ◽  
Vol 4 (2) ◽  
pp. 83-88
Author(s):  
Ridwan Rismanto ◽  
Lucki Darmawan ◽  
Arief Prasetyo
Keyword(s):  
A Priori ◽  
Real Data ◽  
Test Results ◽  
Transaction Data ◽  
Online Purchases ◽  
Sample Data ◽  
Purchasing Patterns ◽  
The City ◽  
Computerized System ◽  
Confidence Value

Progress in Information Technology encourages culinary businesses to innovate, one of them is a computerized system, online-based sales and several interesting features that can increase consumer interest and increase sales to be the most frequently used innovation today. The cafe "Hidden Toast and Float" is a cafe in the City of Kediri. To increase sales from the cafe, a system is needed to facilitate the owner in recording sales and increasing the number of sales by providing automatic menu recommendations to customers. Based on the problem, in this thesis a website-based sales system and sales system will be created that is accompanied by the application of a priori algorithm to determine the purchasing patterns of customers and automatic menu recommendations from the system for customers. The test results of this thesis are two website-based systems with admin systems used to process existing data on the database and customer websites that are used for online purchases, as well as the application of a priori algorithms with the results of testing sample data and real data that produce menu combination recommendations. most often purchased based on all transaction data, namely Dark Choco Jam and Cappucino with a support value of 15% and a confidence value of 45%.

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