Products are goods that are available and provided in stores for sale. Products provided in stores must be arranged properly to order to attract the attention of consumers to buy. Products arranged in a store will depend on the type of store.The product arrangement at a retail store will be different from the product arrangement at a clothing store. Store display will reflect a picture that is in the store so consumers know the types of products sold by product arrangement. An attractive arrangement will stimulate the desire of consumers to buy. In data mining there are several types of methods by use including prediction, association, classification and estimation. In the prediction method there are several techniques including the frequent pattern growth (FP-growth) method. FP-growth algorithm is the development of the apriori algorithm. So, the shortcomings of the apriori algorithm are corrected by the FP-growth algorithm. FP-growth is one alternative algorithm that can be used to determine the set of data that most often appears (frequent itemset) in a data set. Results of research on the application of the FP-growth algorithm to maximizing the display of goods. It is hoped that this research can be used to adjust the product layout according to the level of frequency the product is sought by the customer so that the customer has no difficulty finding the product they want.
The Medan Marelan Health Center is one of the health centers in the city of Medan. The supply of medicines is considered necessary so that these medicines can still be available at any time with various types and functions. In order not to experience difficulties in distributing medicines and anticipating the supply of medicines in the Puskesmas, research was carried out using the Data Mining method. In this study, a test will be carried out on the Association Rule which is used as a solution to problems with the pattern of the drug procurement system, and will display information about the value of support and confidence from each Data Mining process. Tests in this study using Weka Software to determine the procurement of drugs that are often needed. Information obtained from the stages of the FP-Growth Algorithm is to produce patterns in the procurement of medicines, and an itemset combination pattern has been formed using the FP-Growth Algorithm method so that the results of this study can be used in drug supply effectively and efficiently.
<p class="Default"><em>The pattern of using chemicals in the laboratory of PT. PLN (Persero) </em><em>Sektor Pembangkitan </em><em>Belawan Medan is not only to find out what chemicals are used but also to find out the amount of chemicals left so that laboratory officials can properly manage the use of these chemicals. One appropriate way to determine the pattern of use of these chemicals is to use data mining techniques. The Data Mining technique used in this case is the FP-Growth Algorithm. FP-Growth is an alternative algorithm that can be used to determine the most frequent set of data in a data set. The study was conducted using several variables, namely the date and chemicals used. The results of this study are in the form of a chemical usage pattern which is processed using software, namely implementing the FP-Growth algorithm using the concept of FP-Tree development in searching for Frequent Itemset.</em></p><p class="Default"><em> </em></p><pre><em>Keywords: Data Mining, Association Rules, Frequent Itemset, FP-Growth</em></pre>
Patients are the main object who must get the best service at a hospital, because the quality of hospital services determines the recovery of a patient and the quality of the hospital. The quality of hospital services has two components, namely the fulfillment of predetermined quality standards and the fulfillment of patient satisfaction. Hospitals must provide services that focus on patient satisfaction. Improving the quality of health services can be started by evaluating each element that plays a role in shaping patient satisfaction. The application of evaluation measures to patient care in each hospital is needed as an increase in the quality of service to patients. The analysis of the fuzzy associate memory method has the closeness of human reasoning to get solutions to various problems so that they are easy to apply and understand. Utilization of decision support system (DSS) analysis with fuzzy associate memory method can be used as an evaluation of the perception of each consumer complaint to measure the level of patient satisfaction.
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