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<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="ytPwp+T8wA5O35ZguLCsUKDTSgMeb+SB4slpDO7CXdFerKl1Z+1pJjDX8yEF/KxCUXs3wICNesSgtFcqtdVyCA==" /> <meta name="citation_title" content="Market Basket Analysis on Transaction Data Using the Apriori Algorithm" /> <meta name="citation_journal_title" content="Jurnal TAM (Technology Acceptance Model)" /> <meta name="citation_author" content="sri karnila" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm" /> <meta name="twitter:title" content="Market Basket Analysis on Transaction Data Using the Apriori Algorithm" /> <meta name="twitter:description" content="This research aims to get information about the relationship between sales patterns carried out by CV. Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of" /> <meta name="twitter:image" content="https://0.academia-photos.com/30858500/9016749/10059663/s200_sri.karnila.jpg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm" /> <meta property="og:title" content="Market Basket Analysis on Transaction Data Using the Apriori Algorithm" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="This research aims to get information about the relationship between sales patterns carried out by CV. Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of" /> <meta property="article:author" content="https://independent.academia.edu/srikarnila" /> <meta name="description" content="This research aims to get information about the relationship between sales patterns carried out by CV. Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of" /> <title>(PDF) Market Basket Analysis on Transaction Data Using the Apriori Algorithm | sri karnila - Academia.edu</title> <link rel="canonical" href="https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "single_work", 'action': "show", 'controller_action': 'single_work#show', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script> var $controller_name = 'single_work'; var $action_name = "show"; var $rails_env = 'production'; var $app_rev = '9387f500ddcbb8d05c67bef28a2fe0334f1aafb8'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.require = { config: function() { return function() {} } } </script> <script> window.Aedu = window.Aedu || {}; window.Aedu.hit_data = null; window.Aedu.serverRenderTime = new Date(1733034854000); window.Aedu.timeDifference = new Date().getTime() - 1733034854000; </script> <script type="application/ld+json">{"@context":"https://schema.org","@type":"ScholarlyArticle","abstract":"This research aims to get information about the relationship between sales patterns carried out by CV. Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of shopping cart transactions made by customers, namely vehicle parts sales transactions and vehicle repair service transactions. The data collection techniques used are interviews and documentation. The criteria used in this research are a minimum of frequent itemset of 20 transactions with support criteria of 1,7%, confidence value of 40% and lift ratio value above 1. The results of the research have produced 9 sales pattern relationships with the highest confidence of 100%. The results that have been obtained are expected to help the CV. Dian Abadi Jaya workshop in making a decision for the next sale.","author":[{"@context":"https://schema.org","@type":"Person","name":"sri karnila"}],"contributor":[],"dateCreated":"2022-12-07","dateModified":null,"datePublished":null,"headline":"Market Basket Analysis on Transaction Data Using the Apriori Algorithm","inLanguage":"en","keywords":[],"locationCreated":null,"publication":"Jurnal TAM (Technology Acceptance Model)","publisher":{"@context":"https://schema.org","@type":"Organization","name":"Yayasan Pendidikan Startech"},"image":null,"thumbnailUrl":null,"url":"https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm","sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":null}]}</script><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/single_work_page/loswp-102fa537001ba4d8dcd921ad9bd56c474abc201906ea4843e7e7efe9dfbf561d.css" /><link rel="stylesheet" media="all" 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Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of shopping cart transactions made by customers, namely vehicle parts sales transactions and vehicle repair service transactions. The data collection techniques used are interviews and documentation. The criteria used in this research are a minimum of frequent itemset of 20 transactions with support criteria of 1,7%, confidence value of 40% and lift ratio value above 1. The results of the research have produced 9 sales pattern relationships with the highest confidence of 100%. The results that have been obtained are expected to help the CV. Dian Abadi Jaya workshop in making a decision for the next sale.","publisher":"Yayasan Pendidikan Startech","publication_name":"Jurnal TAM (Technology Acceptance Model)"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Market Basket Analysis on Transaction Data Using the Apriori Algorithm","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [30858500]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":95407778,"attachmentType":"pdf"}"><img alt="First page of “Market Basket Analysis on Transaction Data Using the Apriori Algorithm”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/95407778/mini_magick20221207-1-solmmy.png?1670451924" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Market Basket Analysis on Transaction Data Using the Apriori Algorithm</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="30858500" href="https://independent.academia.edu/srikarnila"><img alt="Profile image of sri karnila" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/30858500/9016749/10059663/s65_sri.karnila.jpg" />sri karnila</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">Jurnal TAM (Technology Acceptance Model)</p></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">This research aims to get information about the relationship between sales patterns carried out by CV. Dian Abadi Jaya workshop by using APRIORI algorithms through transaction data sets carried out by customers. The subject of research is a record of shopping cart transactions made by customers, namely vehicle parts sales transactions and vehicle repair service transactions. The data collection techniques used are interviews and documentation. The criteria used in this research are a minimum of frequent itemset of 20 transactions with support criteria of 1,7%, confidence value of 40% and lift ratio value above 1. The results of the research have produced 9 sales pattern relationships with the highest confidence of 100%. The results that have been obtained are expected to help the CV. Dian Abadi Jaya workshop in making a decision for the next sale.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":95407778,"attachmentType":"pdf","workUrl":"https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":95407778,"attachmentType":"pdf","workUrl":"https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="95407778" data-landing_url="https://www.academia.edu/92385486/Market_Basket_Analysis_on_Transaction_Data_Using_the_Apriori_Algorithm" data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="114931136" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/114931136/Market_Basket_Analysis_using_Apriori_Algorithm">Market Basket Analysis using Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="237720281" href="https://independent.academia.edu/DrYojnaArora">Dr. Yojna Arora</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Innovative Research in Computer Science &amp; Technology</p><p class="ds-related-work--abstract ds2-5-body-sm">A Technique that check for dependency for one Data item to another is Association Rule which is an old Data mining approach. Which is used to identify the next product that might interest a customer. The Apriori Algorithm is applied in this for mining frequent products sets and relevant Association rule. With this algorithm we can use this for up-sell and also in cross-sell to show the Association rule with the help of the algorithm. These methods are widely used in global companies, so for the good understanding the companies used the methods to remain up to date that what customers demands with which products. The results helps the big retailers to identify a trend for customers buying patterns, which is very helpful information for the retailers to plan their big business operations.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Market Basket Analysis using Apriori Algorithm","attachmentId":111488001,"attachmentType":"pdf","work_url":"https://www.academia.edu/114931136/Market_Basket_Analysis_using_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/114931136/Market_Basket_Analysis_using_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="88754820" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/88754820/Basket_Market_Analysis_Using_R_Based_Apriori_Algorithm_to_Find_Information_from_Sales_Data">Basket Market Analysis Using R-Based Apriori Algorithm to Find Information from Sales Data</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="99479654" href="https://independent.academia.edu/IrvanSutarha">Irvan Sutarha</a></div><p class="ds-related-work--metadata ds2-5-body-xs">INTERNATIONAL JOURNAL ENGINEERING AND APPLIED TECHNOLOGY (IJEAT)</p><p class="ds-related-work--abstract ds2-5-body-sm">Market Basket Analysis is a data mining technique that is used to determine which products a customer will buy simultaneously by analyzing a list of customer transactions. By knowing these products, an e-commerce system can create or develop a customer profile system and can determine its own customer catalog layout. This journal discusses data mining techniques, with association rules that can help check customer buying behavior and increase sales. The result can provide reference prices for cross selling, designing promotions and placing merchandise in stores increasing sales</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Basket Market Analysis Using R-Based Apriori Algorithm to Find Information from Sales Data","attachmentId":92670222,"attachmentType":"pdf","work_url":"https://www.academia.edu/88754820/Basket_Market_Analysis_Using_R_Based_Apriori_Algorithm_to_Find_Information_from_Sales_Data","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/88754820/Basket_Market_Analysis_Using_R_Based_Apriori_Algorithm_to_Find_Information_from_Sales_Data"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="78003729" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/78003729/Study_of_application_of_data_mining_market_basket_analysis_for_knowing_sales_pattern_association_of_items_at_the_O_Fish_restaurant_using_apriori_algorithm">Study of application of data mining market basket analysis for knowing sales pattern (association of items) at the O! Fish restaurant using apriori algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32637228" href="https://buddhidharma.academia.edu/YohanesIsharianto">Yohanes Isharianto</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Physics: Conference Series, 2019</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Study of application of data mining market basket analysis for knowing sales pattern (association of items) at the O! Fish restaurant using apriori algorithm","attachmentId":85201079,"attachmentType":"pdf","work_url":"https://www.academia.edu/78003729/Study_of_application_of_data_mining_market_basket_analysis_for_knowing_sales_pattern_association_of_items_at_the_O_Fish_restaurant_using_apriori_algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/78003729/Study_of_application_of_data_mining_market_basket_analysis_for_knowing_sales_pattern_association_of_items_at_the_O_Fish_restaurant_using_apriori_algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="8739333" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach">Data Mining in Market Basket Transaction: An Association Rule Mining Approach</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="8929169" href="https://kwasu.academia.edu/SulaimanOlaniyiAbdulsalam">Sulaiman Olaniyi Abdulsalam</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Data Mining in Market Basket Transaction: An Association Rule Mining Approach","attachmentId":35091128,"attachmentType":"pdf","work_url":"https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="83804620" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/83804620/A_Technical_Analysis_of_Market_Basket_by_using_Association_Rule_Mining_and_Apriori_Algorithm">A Technical Analysis of Market Basket by using Association Rule Mining and Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="23540429" href="https://rvsgroup.academia.edu/GracePadma">Grace Padma</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2017</p><p class="ds-related-work--abstract ds2-5-body-sm">Data mining refers to extracting knowledge from large amount of data. Market basket analysis is a data mining technique to discover associations between datasets. Association rule mining identifies relationship between a large set of data items. When large quantity of data is constantly obtained and stored in databases, several industries is becoming concerned in mining association rules from their databases. For example, the detection of interesting association relationships between large quantities of business transaction data can help in catalog design, cross-marketing and various businesses decision making processes. A typical example of association rule mining is market basket analysis. This method examines customer buying patterns by identifying associations among various items that customers place in their shopping baskets. The identification of such associations can assist retailers expand marketing strategies by gaining insight into which items are frequently purchased by c...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Technical Analysis of Market Basket by using Association Rule Mining and Apriori Algorithm","attachmentId":89031927,"attachmentType":"pdf","work_url":"https://www.academia.edu/83804620/A_Technical_Analysis_of_Market_Basket_by_using_Association_Rule_Mining_and_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/83804620/A_Technical_Analysis_of_Market_Basket_by_using_Association_Rule_Mining_and_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="104795393" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/104795393/Market_Basket_Analysis_for_Sales_Transaction_in_Shopping_Stores">Market Basket Analysis for Sales Transaction in Shopping Stores</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="109024939" href="https://independent.academia.edu/OMARKHAIRAN">OMAR KAIRAN</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Academic Research in Business and Social Sciences</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Market Basket Analysis for Sales Transaction in Shopping Stores","attachmentId":104429095,"attachmentType":"pdf","work_url":"https://www.academia.edu/104795393/Market_Basket_Analysis_for_Sales_Transaction_in_Shopping_Stores","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/104795393/Market_Basket_Analysis_for_Sales_Transaction_in_Shopping_Stores"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="83319560" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/83319560/Market_basket_analysis_of_administrative_patterns_data_of_consumer_purchases_using_data_mining_technology">Market basket analysis of administrative patterns data of consumer purchases using data mining technology</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="195040721" href="https://independent.academia.edu/LukmanSamboteng">Lukman Samboteng</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Applied Engineering Science, 2022</p><p class="ds-related-work--abstract ds2-5-body-sm">Food is the ingredient that enables people to grow, develop, and achieve. For this reason, food quality and types of food must be considered so that they are safe for consumption and managed. Some plant-based foodstuffs are often processed and consumed by the community, even the most needed in food processing. In this case, the research was carried out using data mining with market basket analysis algorithms to obtain very valuable information to decide the inventory of the type of material needed. Market Based Analysis method is used to analyze all data and create patterns for each data. One method of Market Based Analysis in question is the association rule with a priori algorithm. This algorithm produces sales transactions with strong associations between items in the transaction which are used as sales recommendations that help users (owners) get recommendations when users see details of the itemset purchased. From the results of the trials in this study, it was found that the g...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Market basket analysis of administrative patterns data of consumer purchases using data mining technology","attachmentId":88703965,"attachmentType":"pdf","work_url":"https://www.academia.edu/83319560/Market_basket_analysis_of_administrative_patterns_data_of_consumer_purchases_using_data_mining_technology","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/83319560/Market_basket_analysis_of_administrative_patterns_data_of_consumer_purchases_using_data_mining_technology"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="76175456" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/76175456/Implementation_of_Data_Mining_in_Shopping_Cart_Analysis_using_the_Apriori_Algorithm">Implementation of Data Mining in Shopping Cart Analysis using the Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="97581427" href="https://fitri.academia.edu/SusyRahmawati">Susy Rahmawati</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Internasional Journal of Data Science, Engineering, and Anaylitics, 2021</p><p class="ds-related-work--abstract ds2-5-body-sm">Market basket analysis is one of the techniques of knowledge mining used in a broad dataset or database to find a collection of items that are interwoven. Generally used in a sale, the most relevant shopping cart data is used. This methodology has been widely applied in different multinational or foreign industries and is very useful in consumer buying preferences. Technology advances change business trends dramatically, shifting customer demands require increased surgical accuracy of business. In this research, the writer wants to analyze the shopping cart using apriori algorithm, with a dataset from the Kaggle web. Using anaconda software features with the Python programming language is expected to create knowledge overwriting consumer buying patterns. In conclusion, this pattern can be used to support industry in managing its company activities.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Implementation of Data Mining in Shopping Cart Analysis using the Apriori Algorithm","attachmentId":83933590,"attachmentType":"pdf","work_url":"https://www.academia.edu/76175456/Implementation_of_Data_Mining_in_Shopping_Cart_Analysis_using_the_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/76175456/Implementation_of_Data_Mining_in_Shopping_Cart_Analysis_using_the_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="29412502" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/29412502/A_Radical_Approach_for_Market_Basket_Analysis_under_the_Framework_of_Binary_Transaction_based_improved_Apriori_Algorithm">A Radical Approach for Market Basket Analysis under the Framework of Binary Transaction based improved Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11565886" href="https://independent.academia.edu/AnupamMondal2">Anupam Mondal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Ijca Proceedings on Computing Communication and Sensor Network 2013, 2013</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Radical Approach for Market Basket Analysis under the Framework of Binary Transaction based improved Apriori Algorithm","attachmentId":49855534,"attachmentType":"pdf","work_url":"https://www.academia.edu/29412502/A_Radical_Approach_for_Market_Basket_Analysis_under_the_Framework_of_Binary_Transaction_based_improved_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/29412502/A_Radical_Approach_for_Market_Basket_Analysis_under_the_Framework_of_Binary_Transaction_based_improved_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="89099119" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/89099119/Sales_Level_Analysis_Using_the_Association_Method_with_the_Apriori_Algorithm">Sales Level Analysis Using the Association Method with the Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9640181" href="https://independent.academia.edu/AsrulSani5">Asrul Sani</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Jurnal Riset Informatika</p><p class="ds-related-work--abstract ds2-5-body-sm">The company does not yet know the pattern of consumer purchases because so far, the sales transaction data has not been used correctly and does not have a unique method to determine consumer buying patterns. To overcome the problems on the company, this research was done to reprocess sales transaction data for 2018-2019 using data mining techniques with association methods and apriori algorithms. RapidMiner is a supporting application used to find association rules derived from transaction data. Processed transaction data using the Knowledge Discovery in Database (KDD) approach. Thus, the company can determine consumer habits in buying goods derived from sales transaction data for 2018-2019. The results of this study are that in 2018, nine association rules were obtained, of which the best were CT G-246 ⇒ CT G-250 and CT G-250 ⇒ CT G-246. In 2019, nineteen association rules were obtained, of which the best were PN 0441, SK 0175 ⇒ SK 0530 and SK 0175, SK 0283 ⇒ SK 0530. From the best...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Sales Level Analysis Using the Association Method with the Apriori Algorithm","attachmentId":92960263,"attachmentType":"pdf","work_url":"https://www.academia.edu/89099119/Sales_Level_Analysis_Using_the_Association_Method_with_the_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/89099119/Sales_Level_Analysis_Using_the_Association_Method_with_the_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":95407778,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":95407778,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_95407778" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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