Companies need several types of communication technology that can predict customer purchase interest, the goal is that the company can properly consider product sales and determine the company's paint product supply. So far, the decision of the Home Smart sales manager has been made by looking at the closeness of the supplier relationship and how many sponsors are funding the company. So that sometimes the product cannot compete with other companies. The Naive Bayes classifier algorithm is one of the algorithms included in the classification technology. The application of the Naive Bayes method is expected to predict paint purchases from suppliers. From 60 paint purchase data tested with the Naive Bayes method, the results reached 80% of the accuracy of the predictions. Of the 60 tested paint purchase data, 48 paint purchase data were successfully classified correctly.

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Many schools need the implementation of articles about the students selection of best transfer Junior High school. In order of fulfil this necessity, we perform a research that giving recommendation of best transfer school for students as a solution by using scientific articles.  The selection need some criterias such as the economics value,study ability, time, and facilities. This research implement Multi-Objective Optimization On The Basic Of Ratio  Analysist (MOORA).The final result of this research is final decision that help selecting best junior high school for students because it give recomendation output from the highest to lowest value of alternative with each criteria in Moora. This research will give best decision in selecting best junior high school transfer as the students expected.

Nafii Store is one of the stores engaged in selling herbal products. With the large number of public requests for herbal products during the COVID-19 pandemic, stock availability is needed to increase sales transactions for these products. To avoid the limited supply of herbs, an information system is needed that can help store leaders to find out what kind of products should be increased in stock according to customer demand. The appropriate application to overcome these problems is the development of the concept of data mining. Based on the Nafii Store herbal sales data sample, which amounted to 24 transactions, this study will use a minimum support = 16% and a minimum confidence = 70%. The results of the determination of the Association Rules and testing with the Tanagra application that the pattern of herbal purchases are: If you buy Baarik Forest Honey 800 grams then buy Baarik Forest Honey 470 grams 80%, If you buy Black Seed with Ajwa Kurma stamps then buy Darusyifa Black Bitter Honey 83.3%, If buy Darusyifa Bitter Black Honey then buy Black Seed with Ajwa Dates stamped 83.3%. The results of this study can be used by the store management to make decisions on the availability of herbal products at the Nafii Store.