![]() ![]() ![]() The verification consisted of querying the Scopus database with previously identified key phrases and then performing trend analysis on the revealed Scopus results. The second research method is the bibliographic verification of the obtained results. This method has been conducted in four steps: search, selection, analysis, and synthesis. The first method is the systematic search in bibliographic repositories aimed at identifying the concepts of big data mining for customer insights. This article adopts two research methods. The main purpose of this paper is to provide a theoretically grounded discussion on big data mining for customer insights, as well as to identify and describe a research gap due to the shortcomings in the use of the temporal approach in big data analyzes in scientific literature sources. So that in the supermarket sales data set that we have analyzed, there are several things that need to be improved. Based on research that has been conducted on supermarket sales data sets, information is obtained from several data mining methods and there is a lack of accuracy of information on the association method. The research method used is qualitative methods in the form of case studies. This study aims to explain and analyze the supermarket transaction history, based on the information obtained from the analysis of data mining methods. ![]() The problem to be investigated in this study is the analysis of the transaction history on the supermarket sales data set using the data mining method, namely classification with the Decision Tree, clustering with K-Means, and association with the Association Rules Algorithm. In the data set we obtained, we have several attributes to complete data needs, namely Invoice_ID, and Ratings etc. The Rapid Miner application has a function to analyze and implement data mining methods on the data set which is the basis of this research. In implementing data mining, we use the Rapid Miner application. From the results of the trials in this study, it was found that the greater the minimum support (minsup) and minimum confidence (minconf), the less time it takes to produce recommendations and the fewer recommendations are given, but the recommendations given come from transactions that often appear.ĭata mining has a role to produce a decision. 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. One method of Market Based Analysis in question is the association rule with a priori algorithm. Market Based Analysis method is used to analyze all data and create patterns for each data. 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. Some plant-based foodstuffs are often processed and consumed by the community, even the most needed in food processing. For this reason, food quality and types of food must be considered so that they are safe for consumption and managed. ![]() Food is the ingredient that enables people to grow, develop, and achieve. ![]()
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