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Technology is very influential in the world of increasingly fierce business competition so that business people must find strategies to increase sales results in the midst of business competition. Ornamental plant sellers must be smart in managing stock and making strategies in selling ornamental plants. Transaction data can be processed into information needed to increase sales results, one of which can be used as an analysis of the rules of the buyer transaction association in purchasing ornamental plants so that it can be processed and can support decision making on ornamental plant supplies and can assist officers in recommending other ornamental plants to buyers in a cross selling strategy. Knowing the ornamental plants that are often purchased will be a top priority that must be provided so that there is no stock shortage. In this case, data mining is needed to manage sales transaction data for ornamental plants at the Sindy Flower Shop using a Hash Based algorithm. Hash Based Algorithm that can optimally determine the frequent itemset of candidate itemset. In its application in determining the rules for selling associations of ornamental plants by applying a Hash Based algorithm to obtain frequent itemsets for the 3-itemset Dahlia, Empasen and Melati which are a combination of 3-itemset ornamental plants which are prioritized in sales with a support value of 25% and confidence of 60%

Retail is an activity that includes the sale and purchase of goods. For retail stores, the continuity of the business processes that are carried out is very dependent on the sale of goods or the purchase of goods from consumers. Retail stores today must have a strategy or a way to increase sales of their goods. One strategy that can be applied in increasing sales is the preparation of the layout of goods. Errors in the preparation of the layout of goods are of course very detrimental to retail stores, these errors can lead to a stagnant sales process or also decreased sales. The arrangement of the layout of goods can be done by looking at the characteristics of the goods purchased by consumers or commonly referred to as goods associations. Data mining is a technique that can be used to process data. In data mining itself there are many ways that are used to solve problems, one of the ways used to solve problems in data mining is the a priori algorithm. The combination of items obtained by consumers buying item A will also buy Item B with a support value of 20% and a confidence value of 50%. Another combination of items is that consumers buying item A also buys item D with a support value of 10% and a confidence value of 25%. The last combination of item sets, namely Consumers buying item B will also buy item D with a support value of 20% and a confidence value of 50%

Mobile is a sophisticated telecommunication tool to be able to interact with fellow human beings where the communication does not look at near or long distances between people who use the cellphone in communicating well. Mobile phones also have very high capabilities, which can be similar to computers, but mobile phones can be taken anywhere because they have a very minimal size and weight compared to computers. For Mobile Users, it seems to be a need for the whole community that has been widely used by all groups ranging from children, teenagers to the elderly. There are new cellphones and there are also used ones, many prefer to buy used cellphones because besides the prices are much cheaper, even the quality is still good. Therefore, a decision support system is needed to make it easier for used cellphone enthusiasts to get cellphones with good quality and specifications. The methods used are VIKOR and WASPAS methods. The selection of used cellphones is carried out based on predetermined criteria. The results of the application of the VIKOR method with the best alternative are on A3 of 0.793 while based on the WASPAS method the best alternative is on A4 with a reference value of 0.886