Completing cat products in meeting consumer demand is something that must be addressed. Sales are very important for sales. The amount of demand for goods increases, it will get a large income. The purpose of this study is to predict the sales revenue of paint products at UD. Masdi Related, makes it easy for the leadership of the company to find out the amount of money obtained quickly. This research also makes it easy for companies to take business strategies quickly and optimally. The data used in this research is the data of paint product sales for January 2016 to December 2018 which is processed using the Monte carlo method. Income prediction will be done every year. In addition to predicting revenue, the sales data is also used to predict product demand every year. To predict the sales of paint products using the Monte Carlo method. The results of this study can predict sales revenue of paint products very well. Based on the results of tests conducted on the system used to predict sales revenue of cat products with an average rating of 89%. With a fairly high degree of accuracy, the application of the Monte Carlo method can be estimated to make an estimate of the income and demand for each paint product every year. Necessary, will facilitate the leadership to choose the right business strategy to increase sales of cat product sales.
Family Planning aims to minimize birth rates in Indonesia. The target of family planning is couples of childbearing age, which refers to a married couple whose wife has a age range of 15-49 years. Contraception itself consists of 2 types of time periods, namely short and long. Where couples of childbearing age can choose according to what they want, therefore there is often a shortage of contraceptive supplies. Thus, it is necessary to predict the use of contraception using a method to be more efficient. The Monte Carlo method is used as a numerical analysis method that involves a random sample of random numbers. Where to use the previous year's data to get predictions of the number of usage of the following year in the form of numbers. And after a series of simulation results have been obtained the percentage results with an average of above 80%.
The high low price of gold influenced by many factors such as economic conditions, inflation rate, supply and demand and much more. The Naïve Bayes algorithm is capable of generating a classification that is used to predict future opportunities. By using the Naïve Bayes Classifier algorithm obtained a prediction of gold prices that can help decision makers in determining whether to sell or buy gold. By using the Naïve Bayes Classifier algorithm obtained a prediction of gold prices that can help decision makers in determining whether to sell or buy gold. Gold data will be processed using Rapidminer software. Stages of processing are reading training data, calculating the mean and standard deviation, entering the test data and finding the density value of gauss and then looking for probability value. Based on the calculation that has been done, Naïve Bayes Classifier method is able to predict the price of gold for 1 day ahead or every day. With the results of this calculation is expected to help gold investment actors in increasing accuracy to predict gold prices for decision making.
Basically grades that do not meet graduation criteria are phenomenon for schools. Which can cause a lack of school quality. One such phenomenon is the National examination Score which is the value of determining graduation for students. Vocatonal High School (SMK) Negeri 2 Pekanbaru is a formal education unit as the organizer of the Teaching Learning Process (TLP), for student afterc ompleting education can go directly to employment or the industrial world and can continue their education. Where the test csores obtained by student are inseparable from the school graduation criteria.To deal whith probalytic situations like this we need a method for analyzing or predict likely in the future. One method that can be used is Monte Carlo Simulation. By using Monte Carlo Simulation to the national exam in this study is expected to holp to find out the acquition of student grades for the future. The csores are taken fom the national exam result obtained from the curriculumsection of the last 3 academic years, namely TP 2016/2017 to TP 2018/2019. This scores is simulationted whith PHP programming as a data implementation system. Simulation result from this studyobtained an accuracy level of 86,68%. By getting a greater degree of accuracy, this method is appropriate to be predict the National Exam Scores for the future.
The availability of red bricks on the market is a problem that must be addressed. Because the availability of red brick affects sales revenue. The purpose of this research in the Small and Medium Micro Business of the Red Brick City of Pariaman is to predict the production of red bricks to find out income and find out the next production. So this research can make it easier for business owners to find out how much it will cost for the next production cost. The data used in this study are production data from 2017 to 2019 which are processed using the Monte Carlo method. Based on the results of production prediction testing that has been done, it is found that the average accuracy is 90%. With the results of a high degree of accuracy, the application of the monte carlo method is considered to be able to predict production annually. Making it easier for business owners to determine the costs incurred in the next production process.
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