Application of Apriori Algorithms to Determine Associations in Outdoor Sports Equipment Stores

Irfiani, Eni

doi:10.33395/sinkron.v3i2.10089

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…Association analysis or association rule mining is a data mining technique to obtain the rules of a combination of items and is useful for finding interesting hidden relationships in large data sets [21] and this method can determine consumer buying behavior patterns [22]. There are two main benchmarks in this association technique, namely: Furthermore, after a combination of 1 item is formed and the item that meets the minimum supply is selected, it is continued by compiling a combination of 2 items until the most n-itemset.…”

Section: Literature Reviewmentioning

confidence: 99%

Pattern Recognition of Customer Spending Habits Using Apriori Algorithms in DataMining as an Inventory Strategy

et al. 2022

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The readiness of product inventory is very important, product shortages related to other products can make buyers disappointed and then cancel to buy products that were previously planned to be purchased at once. Sellers can experience a decrease in the number of sales to revenue. In this case, the seller needs to know the pattern of customer habits when making purchases by going through sales transaction data that has occurred. Association techniques can be used to analyze the pattern of interrelationships between items in transaction events. With the a priori algorithm as a popular association algorithm, the pattern of sales transaction data can be analyzed through the research stage. From the implementation of the algorithm with 1063 transaction data using 10% min-support and 75% min-confidence resulting in 4 association rules where 1) if you buy "kacer" and "love bird" you will buy "pentet" as much as 17% support, 2) if you buy "magpie" and "love bird" will also buy "pentet" at 16%, 3) if you buy "kacer" and "magpie" then you will buy "pentet" at 14%, 4) if you buy "anis" you will buy "pentet" of 11% with a confidence level of 76%, 81%, 84%, 77%, respectively. So, there are 5 main items that play a strong role in the rule that must be considered. Sellers can use the resulting item relationship patterns as consideration in managing inventory and structuring the items sold.

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Section: Literature Reviewmentioning

confidence: 99%

Pattern Recognition of Customer Spending Habits Using Apriori Algorithms in DataMining as an Inventory Strategy

et al. 2022

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“…According to (Irfiani, 2019), "Data mining is a method by extracting large amounts of information, in this way helping companies focus on important information in data warehouses".…”

Section: A Understanding Data Miningmentioning

confidence: 99%

Apriori Algorithm On Car Rental Analysis With The Most Popular Brands

Panjaitan

Handrianto

Nurhadi

2020

SinkrOn

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Nowadays, vehicle rental has become a common function for companies that have busy operational activities. Every company in carrying out operational activities requires a vehicle that is always there when needed. PT. Agung Solusi Trans is a vehicle rental company that rents various vehicle brands commonly used by customers to rent vehicles. In addition, PT. Agung Solusi Trans is also difficult to get updated information regarding the level of sales per period. Therefore, we need a decision support system and a method that can be used to design a business strategy that can provide an efficient and effective information, namely data mining using the a priori algorithm association method. The researcher specializes in taking only vehicle types as research material by selecting fifteen brands, including Agya, Yaris, Sienta, Calya, Avanza, Innova, Rush, Vios, Altis, Camry, Fortuner, Alphard, Hi Ace, Voxy, and Hilux. In analyzing the data, the writer uses a priori algorithm calculation by testing the hypothesis of two variables between the value of support and the value of confidence. After that, apriori algorithm is calculated using Tanagra. Based on the analysis done by the author, that the brands most sought after by customers are Calya, Avanza, Hilux. From these results can be used by PT. Agung Solusi Trans to prepare vehicle brands that are widely leased by customers and increase brand inventory.

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“…These two algorithms have the same goal of finding patterns in datasets, but apriori and FP-Growth algorithms have different approaches and techniques for extracting relevant information from data. Natural inventory control [37]- [40].…”

Section: Introductionmentioning

confidence: 99%

Implementation of association rule using apriori algorithm and frequent pattern growth for inventory control

Riadi,

Herman,

Fitriah

et al. 2023

J.INFOTEL

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Business success is a business that is able to compete and grow keep abreast of developments in the business world. Especially in the retail sector, where competition is getting tighter. Business owners need to pay attention to the layout of goods and stock management to improve service and meet consumer needs because consumers often have difficulty in finding goods. On the other hand, shortages and excess stock often occur due to lack of goods management. Based on these problems, appropriate techniques are needed for the management of goods supply, one of which is to apply techniques found in the branch of science. Data mining is a technique of association rules. This study aims to find patterns of placement and purchase of goods in generating Association Rule using FP-Growth algorithm. The dataset in this study used data on sales of goods in clothing stores. The results of the study of 140 transactions there are 24 association rules consisting of 7 association rules with 2-itemsets and 17 association rules with 3-itemsets that most often appear in transactions. Based on the order of the highest support value, namely CKJ→STX^LK with a support value of 67%, while the highest confidence value, there are 3 association rules that get the same value, namely STX^CKJ→LK, STX^CAK→LK, STX^RI→LK with a value of 100%. Thus, the rules of association produced by the frequent itemset algorithm, FP-growth, can serve as decision support for the sales of goods in small and medium-sized retail businesses

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Application of Apriori Algorithms to Determine Associations in Outdoor Sports Equipment Stores

Cited by 7 publications

References 5 publications

Pattern Recognition of Customer Spending Habits Using Apriori Algorithms in DataMining as an Inventory Strategy

Pattern Recognition of Customer Spending Habits Using Apriori Algorithms in DataMining as an Inventory Strategy

Apriori Algorithm On Car Rental Analysis With The Most Popular Brands

Implementation of association rule using apriori algorithm and frequent pattern growth for inventory control

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