利用电子DHURROH商店的杏算法挖掘数据的方法

Syafrianto Syafrianto, Durotun Ayniyah
{"title":"利用电子DHURROH商店的杏算法挖掘数据的方法","authors":"Syafrianto Syafrianto, Durotun Ayniyah","doi":"10.30736/jt.v13i2.624","DOIUrl":null,"url":null,"abstract":"In the business world, every store must of course be able to compete and think about how the store can continue to grow and be able to expand its business scale. In order to increase sales of products sold, business actors must have various strategies. One way is by utilizing all sales transaction data that has occurred in the store itself. Dhurroh Elektronik store is a store that sells various kinds of goods such as cellphone accessories. Management of sales data in this store is still done manually, namely by recording sales data in the sales book or sometimes when serving purchases just remembering it. The obstacle faced is that it is difficult to find out where the goods are not in accordance with the behavior of consumers' habits in buying goods at the same time. Based on the above problems, it is necessary to have a calculation to group data items based on their tendencies that appear together in a transaction with Data Mining calculations using the Apriori Algorithm method. The results of the calculation of the items that are most in-demand are if you buy a headset, you will buy a lamp with a 100% confidence value and 19% support, if you buy a radio you will buy a lamp with a 71% confidence value and 16% support, if you buy a data cable, you will buy a flashlight. with a 71% Confidence value and 16% Support, If you buy a battery, you will buy a Flashlight with a 71% Confidence value and 16% Support. Keywords: Data Mining, Apriori Algorithm..","PeriodicalId":17707,"journal":{"name":"Jurnal Qua Teknika","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"IMPLEMENTASI DATA MINING MENGGUNAKAN METODE ALGORITMA APRIORI PADA TOKO DHURROH ELEKTRONIK\",\"authors\":\"Syafrianto Syafrianto, Durotun Ayniyah\",\"doi\":\"10.30736/jt.v13i2.624\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the business world, every store must of course be able to compete and think about how the store can continue to grow and be able to expand its business scale. In order to increase sales of products sold, business actors must have various strategies. One way is by utilizing all sales transaction data that has occurred in the store itself. Dhurroh Elektronik store is a store that sells various kinds of goods such as cellphone accessories. Management of sales data in this store is still done manually, namely by recording sales data in the sales book or sometimes when serving purchases just remembering it. The obstacle faced is that it is difficult to find out where the goods are not in accordance with the behavior of consumers' habits in buying goods at the same time. Based on the above problems, it is necessary to have a calculation to group data items based on their tendencies that appear together in a transaction with Data Mining calculations using the Apriori Algorithm method. The results of the calculation of the items that are most in-demand are if you buy a headset, you will buy a lamp with a 100% confidence value and 19% support, if you buy a radio you will buy a lamp with a 71% confidence value and 16% support, if you buy a data cable, you will buy a flashlight. with a 71% Confidence value and 16% Support, If you buy a battery, you will buy a Flashlight with a 71% Confidence value and 16% Support. Keywords: Data Mining, Apriori Algorithm..\",\"PeriodicalId\":17707,\"journal\":{\"name\":\"Jurnal Qua Teknika\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Qua Teknika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30736/jt.v13i2.624\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Qua Teknika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30736/jt.v13i2.624","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在商业世界中,每个商店当然必须能够竞争,并考虑如何使商店继续增长,并能够扩大其业务规模。为了增加销售产品的销售额,业务参与者必须有各种策略。一种方法是利用商店本身发生的所有销售事务数据。Dhurroh Elektronik商店是一家销售手机配件等各种商品的商店。这家商店的销售数据管理仍然是手工完成的,即通过在销售簿中记录销售数据,或者有时在服务购买时只是记住它。面临的障碍是很难发现商品在哪里不符合消费者在购买商品时的习惯行为。基于上述问题,有必要使用Apriori算法方法进行数据挖掘计算,根据在事务中一起出现的趋势对数据项进行分组。最受欢迎的物品的计算结果是,如果你买耳机,你会买一个100%置信度和19%支持度的灯,如果你买收音机,你会买一个71%置信度和16%支持度的灯,如果你买数据线,你会买一个手电筒。如果你买了电池,你将买到一个具有71%置信度值和16%支持度的手电筒。关键词:数据挖掘;Apriori算法;
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMPLEMENTASI DATA MINING MENGGUNAKAN METODE ALGORITMA APRIORI PADA TOKO DHURROH ELEKTRONIK
In the business world, every store must of course be able to compete and think about how the store can continue to grow and be able to expand its business scale. In order to increase sales of products sold, business actors must have various strategies. One way is by utilizing all sales transaction data that has occurred in the store itself. Dhurroh Elektronik store is a store that sells various kinds of goods such as cellphone accessories. Management of sales data in this store is still done manually, namely by recording sales data in the sales book or sometimes when serving purchases just remembering it. The obstacle faced is that it is difficult to find out where the goods are not in accordance with the behavior of consumers' habits in buying goods at the same time. Based on the above problems, it is necessary to have a calculation to group data items based on their tendencies that appear together in a transaction with Data Mining calculations using the Apriori Algorithm method. The results of the calculation of the items that are most in-demand are if you buy a headset, you will buy a lamp with a 100% confidence value and 19% support, if you buy a radio you will buy a lamp with a 71% confidence value and 16% support, if you buy a data cable, you will buy a flashlight. with a 71% Confidence value and 16% Support, If you buy a battery, you will buy a Flashlight with a 71% Confidence value and 16% Support. Keywords: Data Mining, Apriori Algorithm..
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信