IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/96524.html
   My bibliography  Save this paper

Prediksi Pendapatan Terbesar pada Penjualan Produk Cat dengan Menggunakan Metode Monte Carlo
[Prediction of the Biggest Revenue in the Sales of Cat Products Using the Monte Carlo Method]

Author

Listed:
  • Geni, Bias Yulisa
  • Santony, Julius
  • Sumijan, Sumijan

Abstract

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.

Suggested Citation

  • Geni, Bias Yulisa & Santony, Julius & Sumijan, Sumijan, 2019. "Prediksi Pendapatan Terbesar pada Penjualan Produk Cat dengan Menggunakan Metode Monte Carlo [Prediction of the Biggest Revenue in the Sales of Cat Products Using the Monte Carlo Method]," MPRA Paper 96524, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:96524
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/96524/1/4
    File Function: original version
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Modeling and Simulation; Monte Carlo; Revenue Prediction; Paint Products; Building Stores;
    All these keywords.

    JEL classification:

    • G0 - Financial Economics - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:96524. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.