IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/5u9ns_v1.html
   My bibliography  Save this paper

Analisa Data Dengan Metode Least Square Untuk Prediksi Penjualan Sepeda Motor (Studi Kasus: PT. Jaya Abadi Motor)

Author

Listed:
  • Zulkifli, Achmad
  • Wandana, Adhitya Yoga
  • Firnadi, Muhammad Rasyad Zafran
  • Rafli, Muhammad

Abstract

PT. Jaya Abadi Motor is an authorized dealer for Yamaha motorbikes. This company experienced an increase in motorcycle sales for each year. In this connection it is necessary to predict the number of motorcycle sales in the coming period.

Suggested Citation

  • Zulkifli, Achmad & Wandana, Adhitya Yoga & Firnadi, Muhammad Rasyad Zafran & Rafli, Muhammad, 2020. "Analisa Data Dengan Metode Least Square Untuk Prediksi Penjualan Sepeda Motor (Studi Kasus: PT. Jaya Abadi Motor)," OSF Preprints 5u9ns_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:5u9ns_v1
    DOI: 10.31219/osf.io/5u9ns_v1
    as

    Download full text from publisher

    File URL: https://osf.io/download/5fe97fcee9ccb9020aaee2c1/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/5u9ns_v1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    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:osf:osfxxx:5u9ns_v1. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.