scholarly journals Analysis of Data Mining Associations on Drug Sales at Pharmacies with APRIORI Techniques

2021 ◽  
Vol 5 (1) ◽  
pp. 38
Author(s):  
Salam Irianto Nadeak ◽  
Yusmar Ali
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Marketing Strategies ◽  
Test Results ◽  
Minimum Support ◽  
Artificial Intelligence Techniques ◽  
Drug Sales ◽  
Association Method ◽  
Product Promotion

The purpose of the research is to utilize artificial intelligence techniques in analyzing drug sales. Sources of data used are observations and interviews with shop owners. The method used as a solution is the Association method with the Apriori technique. By using the RapidMiner software, the test results are obtained using a minimum support of 25% and a minimum of 60% confidence as many as 5 rules with a predetermined itemset. The results of the study are expected to provide information and make it easier for related parties to find combinations of selling items. The results of this analysis can be used by pharmacies for marketing strategies and product promotion.

Strategic Utilization of Data Mining

2005 ◽  
pp. 2638-2642
Author(s):  
Chandra S. Amaravadi
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Support ◽  
Information Systems ◽  
Relational Databases ◽  
Online Analytical Processing ◽  
Artificial Intelligence Techniques ◽  
The Past ◽  
Analytical Processing

In the past decade, a new and exciting technology has unfolded on the shores of the information systems area. Based on a combination of statistical and artificial intelligence techniques, data mining has emerged from relational databases and Online Analytical Processing as a powerful tool for organizational decision support (Shim et al., 2002).

scholarly journals Pola Beli Konsumen Menggunakan Algoritma Fp-Growth Untuk Rekomendasi Promosi Pada Aneka Jaya Motor

2021 ◽  
Vol 6 (1) ◽  
pp. 48-55
Author(s):  
Junta Zeniarja
Keyword(s):  
Data Mining ◽  
Business Strategy ◽  
Recommendation System ◽  
Transaction Data ◽  
Data Mining Techniques ◽  
Minimum Support ◽  
Spark Plug ◽  
Using Data ◽  
Product Promotion

A piece of appropriate information can create and establish a business strategy in increasing sales through technology that can affect the trade-in buying and selling goods with the data information generated can be calculated in detail and accurately. At Aneka Jaya Motor Semarang, this was triggered by the demand for competition. One solution is a product promotion target. For determining which items are feasible for promotion, the application of a promotional decision recommendation system is made using data mining techniques associated with FP-Growth algorithms, its function is to find items that are often purchased simultaneously by consumers. Data used in the form of transaction data with the total amount used 501 data. The results obtained by appearing 1 rule is if consumers buy spark plug parts then buy oil parts with minimum support of 10% and minimum confidence of 35%. The lift ratio obtained is 1 so that valid rules are generated.

scholarly journals MARKET BASKET ANALYSIS USING THE FP-GROWTH ALGORITHM TO DETERMINE CROSS-SELLING

2021 ◽  
Vol 7 (4) ◽  
pp. 49-54
Author(s):  
Fildzah Zia Ghassani ◽  
Asep Jamaludin ◽  
Agung Susilo Yuda Irawan
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Basic Needs ◽  
Market Basket Analysis ◽  
Rice Cake ◽  
Market Basket ◽  
Transaction Data ◽  
Minimum Support ◽  
A Value ◽  
Association Method

KAOCHEM Sinergi Mandiri Cooperative is a cooperative that provides various kinds of basic needs such as basic foodstuffs that can meet the needs of its members. The cooperative transaction data is only stored as a report. Association rules are a method in data mining that functions to identify items that have a value that is likely to appear simultaneously with other items. One implementation of the association method is Market Basket Analysis. The data used are transaction data for November 2019. Data mining is one of the processes or stages of the KDD method. The data mining process is carried out using the FP-Growth algorithm, which is one of the algorithms for calculating the sets that often appear from data. Researchers analyzed transaction data using the Rapid Miner Studio tools. In the data mining process using FP-Growth the researcher determines a minimum support value of 3% and a minimum confidence of 50%. The association process using these values ​​produces 3 strong rules, namely if ades 350 ml, then fried / lontong with a support value of 0.030 and confidence 0.556 and if fried st, then fried / lontong with a support value of 0.048 and confidence 0.639, and if nasi uduk / bacang , then fried / rice cake with a support value of 0.031 and confidence 0.824. The results of the association rules can be applied using one of the marketing techniques, namely cross-selling to increase the sales of the cooperative.

Strategic Utilization of Data Mining

2008 ◽  
pp. 1689-1695
Author(s):  
Chandra S. Amaravadi
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Support ◽  
Information Systems ◽  
Relational Databases ◽  
Online Analytical Processing ◽  
Artificial Intelligence Techniques ◽  
The Past ◽  
Analytical Processing

In the past decade, a new and exciting technology has unfolded on the shores of the information systems area. Based on a combination of statistical and artificial intelligence techniques, data mining has emerged from relational databases and Online Analytical Processing as a powerful tool for organizational decision support (Shim et al., 2002).

scholarly journals Prediction of Infertility Treatment Outcomes Using Classification Trees

2016 ◽  
Vol 47 (1) ◽  
pp. 7-19 ◽  
Author(s):  
Anna Justyna Milewska ◽  
Dorota Jankowska ◽  
Urszula Cwalina ◽  
Dorota Citko ◽  
Teresa Więsak ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
In Vitro Fertilization ◽  
Treatment Outcomes ◽  
Classification Trees ◽  
Infertility Treatment ◽  
Vitro Fertilization ◽  
Artificial Intelligence Techniques ◽  
Mining Methods

Abstract Infertility is currently a common problem with causes that are often unexplained, which complicates treatment. In many cases, the use of ART methods provides the only possibility of getting pregnant. Analysis of this type of data is very complex. More and more often, data mining methods or artificial intelligence techniques are appropriate for solving such problems. In this study, classification trees were used for analysis. This resulted in obtaining a group of patients characterized most likely to get pregnant while using in vitro fertilization.

scholarly journals Application of Data Mining on Sales of Leather Handicrafts in Sidoarjo with Apriori Algorithm to Help Marketing Strategy

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Muhammad Alfin Firdiansyah ◽  
Yulian Findawati ◽  
Cindy Taurusta ◽  
Ade Eviyanti
Keyword(s):  
Association Rule ◽  
Small And Medium Enterprises ◽  
Forward Direction ◽  
Marketing Strategies ◽  
Apriori Algorithm ◽  
Test Results ◽  
Minimum Support ◽  
Tourism Sector ◽  
Combination System ◽  
Medium Enterprises

Sidoarjo is one of the regencies that is developing in a forward direction. This is known by the increase in the tourism sector and Small and Medium Enterprises. One of them is Sidoarjo leather handicraft. UD Qory Jaya is a business actor in the leather retail industry. Orders that continue to increase make the turnover of goods uneven resulting in a buildup of stock in stores. Due to these problems the compilers took the initiative to deliver messages by carrying out a method of processing data using the Apriori algorithm. This method is used to maximize the sales potential of a combination system of goods so that the target item for sale is appropriate. From the results of research conducted by testing a minimum support of 15% and a minimum of 20% confidence, the association rules are produced if you buy a slingbag then buy men's leather shoes and vice versa. And from the test results with a minimum support of 70% and a minimum confidence of 70% an association rule is not generated because the existing data does not exceed the minimum value of support and minimum confidence. With the implementation of this method, researchers hope to have a better impact for developing future marketing strategies based on previously researched data.

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

Sign in / Sign up

Export Citation Format

Share Document