Artificial Neural Network (ANN) technique has developed rapidly in the field of estimation. ANN can predict based on data on events and related factors that existed in the past. ANN has advantages in parallel computing in classifying patterns. ANN is also capable of self-regulating the data to be processed without requiring an explicit function specification. The advantage of using ANN is the elimination of complex analytical and numerical iterative computations. The ANN method that is often used in prediction case studies is the Backpropagation Algorithm. This algorithm has the ability to solve problems in the real world by building trained methods that show good performance on large data scales and are able to overcome complex pattern recognition. This study aims to predict the demand for salt optimally using the ANN Method with the Backprogation Algorithm at PT. Kurnia Garam Prosperous Padang City. This forecasting is needed because of the high cost of production with the large number of requests that occur to be more effective. Proper forecasting will be able to optimize production so that it can reduce the required production costs. The data processed is salt production data from 2016 to 2018 at PT. Kurnia Garam Prosperous. The momentum results obtained are 3-9-1 for dividing the data into 2, namely 24 training data and 12 test data. The optimal prediction result is 0.98946, so this research is very helpful in forecasting optimal and efficient production costs.
The increasing need for salt in the West Sumatra area is inversely proportional to the raw material for making salt. So the stock of salt for consumption becomes less. This causes the purchasing power to be cut off for the needs of regional consumers. Based on these problems, a research was conducted by conducting simulations to predict the amount of salt sales in controlling stock. This study aims to predict sales in maintaining service to consumer demand. The method that can be used in making predictions is the Monte Carlo Method by processing Salt sales data in 2019, 2020, and 2021 at PT. Prosperous Grace. The results of the study are able to predict sales of salt in the form of kilograms (kg) in the future. The average accuracy rate in 2020 is 88% and in 2021 is 91%. So that this research can be a reference in decision making by PT. Kurnia Sejahtera to improve services.
Simulation modeling is used as a tool to see a picture of the company's condition in the future and as a forum for making a decision. Currently, sales are an important activity and a factor that must be considered in future planning. The purpose of sales is to bring profit or profit from products or services produced with good management. Simulation can help solve everyday problems such as existing problems, with simulation applications estimating the number of sales is very important. If someone can predict the number of sales, the cost of procurement and storage of goods can be minimized. From this, several parties can bring in profits as much as possible, and minimize losses. There are 18 sales sample data processed in this study, namely sales data from 2021 to 2022. Sales data is processed using the Monte Carlo method from January 2021 to June 2021 to predict results for July to December 2021. Then for July to December 2021 to predict the results for January to June 2022. The data is tested with various elements of probability using a random sample. A powerful numerical calculation tool by simulating statistical data, this simulation obtains accurate accuracy values from the observable physical form of the system. Implementation of calculations will be developed using an application-based system that will be built with the JAVA programming language. The test results that have been obtained in the form of the average number of product requests and average income will be used as an estimate of sales (state estimate) that can assist in making decisions based on the information that has been obtained. The data obtained has an accuracy rate of up to 80%.
The importance of the soft skills of high school students today tends to be a social concern. Judging from the development of digitalization of existing media, high school students need to prepare and equip themselves to face the rhythm of learning in higher education, or be ready to enter the community with all their competencies. The purpose of this service is to provide assistance for high school students and/or equivalent to Madrasah Aliyah (MA) in the process of making short films. The service is carried out in two stages and is located at MAN 1 Special Program (PK) Surakarta. Through this service, the participants were given material about the initial concept of making a short film, as well as a number of stages in making a short film. Then, participants were asked to practice some simple techniques in taking pictures on film, and continued with the process of making short films. Overall, the participants are expected to have the ability and knowledge of how to make a short film, starting from drafting concepts and story ideas, making scripts, the execution process in shooting, as well as editing and the final stage.
The research aims to determine the impact of the value and quality of goods on satisfaction in buying products at PT. Lancaster Nusantara Cigarindo Lampung. To test the feasibility of the regression test on the impact of value determination and the quality of goods simultaneously on purchasing policies at PT. Lancaster Nusantara Cigarindo Lampung. The population in this study are consumers of PT. Lancaster Nusantara Cigarindo Lampung, a total of 200. So that the items obtained were 91 respondents using the double linear regression hypotensive test. The analysis tools used in this research are validity, reliability, multiple linear regression, correlation coefficient, and determination. The results of research on pricing and quality of goods have a partial effect on purchasing policies that have been carried out, the results of the fcount test exceed the ftable (86.125> 2.06). It can be said that the quality of goods and pricing will affect the simultaneous buying policy. Keywords: Price, Product Quality, Purchase Decision
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