Application of Association Rule Method Using Apriori Algorithm to Find Sales Patterns Case Study of Indomaret Tanjung Anom

Santoso, M. Hamdani

doi:10.47709/brilliance.v1i2.1228

Cited by 33 publications

(15 citation statements)

References 35 publications

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“…Association rules are a powerful technique in data mining and machine learning used to discover interesting relationships or associations between different items in a large dataset. 40 The basic form of an association rule is represented as “A > B”, where A is the previous item and B is the posterior item. The support and confidence values associated with the rule indicate the significance and reliability of the discovered association.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Traditional Chinese Medicine Symptoms in Children with Spastic Cerebral Palsy, a Protocol for Data Mining

Wang,

Pang,

2023

JMDH

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Background Cerebral palsy (CP) is characterized by abnormal pronunciation, posture, and movement. Clinically, CP can be categorized into various motor syndromes, including spastic hemiplegia, diplegia, quadriplegia, involuntary movement, ataxia, and mixed types. Among these, spastic CP represents over 70–80% of all CP cases. The primary objective of our study is to identify the top and core Traditional Chinese Medicine (TCM) symptoms and analysis their association rules in children with spastic cerebral palsy, thereby enhancing the theoretical foundations of TCM treatment on spastic CP. Methods The study will be conducted on children aged 4 to 14 years with spastic CP who are undergoing treatment at Xi’an Encephalopathy Hospital Affiliated to Shaanxi University of Chinese Medicine. Basic information about the patients and their TCM symptoms will be collected on the first day of admission. This information will include age, gender, birth history, family history, disease classification, and TCM symptoms (including symptoms, tongue, and pulse). Once the data is collected, it will be exported from the electronic medical record system for further analysis. Descriptive statistics will be performed using Excel 2019, while exploratory factor analysis and cluster analysis will be conducted using SPSS Statistics 22. Additionally, association rule analysis will be carried out using SPSS Modeler 18. Results This study will investigate the most top TCM symptoms in children with spastic CP and explore the association rules between these symptoms, mapping the presentation of spastic CP onto symptoms identified within TCM. Conclusion Our findings will provide the distinctive characteristics of TCM symptoms in children with spastic CP, furnishing evidence-based support to clinicians and patients in making well-informed decisions collaboratively.

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Section: Discussionmentioning

confidence: 99%

Analysis of Traditional Chinese Medicine Symptoms in Children with Spastic Cerebral Palsy, a Protocol for Data Mining

Wang,

Pang,

2023

JMDH

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“…One approach used in data mining to locate frequent items/itemsets in transactional databases is the Apriori algorithm. To determine the most common entry from a database, R. Agarwal and R. Srikant invented the a priori algorithm [14]. There are parameter support and confidence.…”

Section: Apriorimentioning

confidence: 99%

Analysis of Stunting Factors in Toddlers Using Data Mining Method the Apriori Algorithm

Hasani,

Yudianto,

Sukmasetya

2024

E3S Web Conf.

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Stunting is one of the developmental problems in children which is influenced by many factors. Experts of nutrition mention several influencing factors such as nutrition during pregnancy, the mother's knowledge about nutrition, limited access to services, and inadequate access to sanitation and water hygiene. These patterns will be analyzed using a data mining method. In this study, 557 stunting data in Jakarta will be analyzed. The data mining method used is the association rule with the a priori algorithm. The steps taken are to perform data cleaning, data integration, data transformation, data mining, and pattern evaluation. There are many attributes in the data studied, but it is determined that several attributes are appropriate to obtain optimal results. The attributes taken are adjusted to research from the health sector. The test results produce several association rules. From all the association rules obtained using the Apriori algorithm, it is taken that meets a minimum support of 0.2 and a minimum confidence of 0.5. There is a result of 73% of the total meeting the minimum support and confidence. So that the results of the association rules can be used by health experts and stakeholders as a reference in determining policy.

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“…Penerapan algoritma apriori dari hasil uji menampilkan ketentuan asosiasi, jika pelanggan kerap membeli pasta gigi serta deterjen maka sudah memenuhi ketentuan nilai kepercayaan (confidence) minimum. Perbedaannya dengan riset ini terletak pada obyek riset, informasi serta fitur dalam perangkat lunak yang digunakan [13].…”

Section: IIunclassified

Komparasi Metode Apriori dan FP-Growth Data Mining Untuk Mengetahui Pola Penjualan

Purwati,

Pedliyansah,

Kurniawan

et al. 2023

JPIT

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Sales data is generally still rarely used, as well as the Perfume Corner shop just piling up in the database, even though there are problems experienced by the store regarding sales data for the best-selling products and to increase the number of sales of subsequent perfume products, so that the store can survive and develop even better. The algorithm that can be used to manage sales data to overcome this problem is Apriori. The research method used in this research is the KDD (Knowledge Discovery in Database) process. This research produces a high frequency pattern for itemsets with a minimum support value of 20% resulting in products that become The Most Tree Items namely Jo Malone 82.49%, Zarra 28.25%, and Zwitsal 20.34%. While the association rules formed from the value of Min. Supp 20% and Min. Conf 80%, get a combination of 2 itemsets, namely Jo Malone and Zarra. Whereas for the combination of 3 itemsets, namely Jo Malone, Zarra and Baccarte with valid and strong status, it is proven by a lift value greater than 1, therefore the association rules are very appropriate to be used.

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Application of Association Rule Method Using Apriori Algorithm to Find Sales Patterns Case Study of Indomaret Tanjung Anom

Cited by 33 publications

References 35 publications

Analysis of Traditional Chinese Medicine Symptoms in Children with Spastic Cerebral Palsy, a Protocol for Data Mining

Analysis of Traditional Chinese Medicine Symptoms in Children with Spastic Cerebral Palsy, a Protocol for Data Mining

Analysis of Stunting Factors in Toddlers Using Data Mining Method the Apriori Algorithm

Komparasi Metode Apriori dan FP-Growth Data Mining Untuk Mengetahui Pola Penjualan

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