Akrim Teguh Suseno, Abdul Razak Naufal, Mohammad Al Amin
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引用次数: 0

摘要

2019冠状病毒病大流行严重影响了印尼的经济。强调通过执行对社区活动的限制来发展covid-19,对中小微企业(MSME)部门产生了影响,包括分销部门的产品销售。因此,需要一种策略来增加销售,其中之一是通过基于市场分析的数据挖掘技术。数据挖掘是数据库中知识发现的过程之一,在应用中采用科学的方法。本研究使用的数据为6531笔销售交易。本研究使用的数据挖掘算法是K-Medoids进行分组,目的是寻找最佳聚类。采用K-3、K-4、K-5、K-6和K-7进行聚类实验,采用Davies Bouldien Index (DBI)方法进行聚类检验,结果表明,聚类K-3均匀性最低,为最佳聚类。关联规则采用FP-Growth算法,最小支持度为6% ~ 7%,最小置信度为60%。关联规则分析的结果是产品推荐,可以用作促销以增加分销商的销售。产品有SE128、SE131、SE130、SE431、SE792、SE804。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MARKET BASED ANALYSIS SEBAGAI PENINGKATAN PENJUALAN PRODUK MENGGUNAKAN ALGORITMA K-MEDOIDS DAN FP-GROWTH
The COVID-19 pandemic has greatly affected the economy in Indonesia. The emphasis on the development of covid-19 through Enforcement of Restrictions on Community Activities has an impact on the Micro, Small and Medium Enterprises (MSME) sector, including product sales at the Distro Sextors. Therefore, a strategy is needed to increase sales, one of which is through data mining techniques with market based analysis. Data mining is one of the processes of Knowledge Discovery in Database (KDD) that uses scientific methods in its application. The data used in this study were 6531 sales transactions. The data mining algorithm used in this research is K-Medoids for grouping which aims to find the best cluster. The cluster experiments used are K-3, K-4, K-5, K-6 and K-7 then cluster testing is carried out using the Davies Bouldien Index (DBI) method and the results are cluster K-3 is the best cluster because it has a homogeneous value lowest. Then the association rule uses the FP-Growth algorithm and the minimum support value used is 6% to 7% while the minimum confidence value is 60%. The results of the association rule analysis are product recommendations that can be used as promotions to increase sales in Distro Sextors. The products are SE128, SE131, SE130, SE431, SE792, dan SE804.
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