Business location plays an important role in sales. The business location in cities makes the seller easier to distribute activities for people. Distribution activities are closely related to sales activities. If there is a sales transaction, a classification of potential and non-potential customers will be required. One method that can be used for classification is mining data. One of the most frequently used data mining for classification is the Naive Bayes method. The attributes used in the customer classification process are purchase amount, time interval, and location. The result of the classification system is 23 true reactions and 2 false reactions. Based on the results are using the confusion matrix method, it shows that the accuracy value reaches 92%, the precision value reaches 100%, the recall value reaches 91%.Keywords: Trading Business, Customer Classification, Naive Bayes, Confusion Matrix
One of the important thing in business is the inventory of goods and services. Business goal can be reached when business owner know how the number of their inventory. Printing business is using forecasting model in their purchasing raw materials to estimate and calculate their selling prediction. That model is used to minimize economic losses when the costumer canceled order because paper was ran out and to prevent paper damage does not occur date to storage that to long. Double Exponential Smoothing method is used in this research to predict the sales of Paper A and HVS A3+ paper and calculates the prediction error with MAPE (Mean Absolute Percentage Error). This study aims to make an accurate forecasting application. The prediction results from application are in the form of prediction calculations for sales in the following month which will be used to optimize the purchase of paper to be sold. In applying the research results of Paper A and HVS A3 +, the best alpha was obtained in the 12th period, namely 0.3 and 0.6 with a MAPE error of 12% and 18% and an accuracy rate of 88% and 82% where the alpha was used to predict period 13 and produces a forecast value of 446 for Paper A and 474 for HVS A3 +
Recommendations are application models from previous measurement of data and information. To process data that is quite a lot is used the right method. Association rules are one technique that can be used in associating indirect data from a data. The purpose of this study is to create a system that can be used to provide information on goods in accordance with consumer combinations. The method used is direct interviews with staff to get information in the form of sales data and system requirements. The design model uses the System Development Life Cycle (SDLC), namely Analysis, Design, Construction, Implementation, and Testing. The system design method used is UML (Unified Modeling Language). The system used is an algorithm that is made web-based using the language PHP and MySQL as databases. The results used in this study are to stop at the specified 2-item iteration and two rules that meet minimum 30% support rules and a minimum confidence of 70%, namely Cofemix → Sugar and Sugar → Sugar.
<p><strong>A</strong><strong>bstract</strong><strong>.</strong> Employees are one of the company's assets that must be managed properly. Therefore the selection of the best employees is now needed. The problem faced in determining the best and qualified employees is that there are still no standards in assessing only one person subjectively in determining the best employee, which consequently lacks appropriate or objective results. To provide rewards for the best employees, we need a system to support the decisions of the best employees who deserve to receive rewards to be on target. The purpose of this research is to design and build a decision support system application in determining the best employees using the analytic hierarchy process and weighted product methods. Stages of software development of the Software Development Life Cycle (SDLC) uses a waterfall, that is data analysis, system design, construction, coding, testing and implementation. The results of this process are in the form of calculation applications that have been obtained from the analytic hierarchy process and weighted product methods in determining the best employee. The result gives an accuracy rate of 82.3%.</p><p><strong>Keywords</strong><strong>: </strong>analytic hierarchy process, weighted product, decision support system, employees</p>
<p>Crimes occur in many places and cause complex problems that have widespread impacts on all levels of society. Crime is related to several factors including crime index, the ratio of the number of police to the population, population density and poverty rates. In this study trying to develop an information system that is able to display and map crime-prone areas in Central Java. Based on these factors, it is used to classify regions in Central Java, namely the category of safe, quite vulnerable, vulnerable and very vulnerable. <em>K</em>-Means clustering method, is very suitable to be used in predicting and grouping which areas are included in the 4 categories. The formulation of the problem is to find out areas prone to crime in Central Java. Based on the results, there are 11 regions with safe categories, 4 areas with quite vulnerable categories, 13 regions with vulnerable categories and 6 regions with very vulnerable categories.</p><p><strong>Keywords</strong><strong> : </strong><em>K</em>-Means clustering, mapping, Central Java, criminality, crime area.</p>
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