View Item 
      •   UMY Repository
      • 03. DISSERTATIONS AND THESIS
      • Students
      • Undergraduate Thesis
      • Faculty of Engineering
      • Department of Electrical Engineering
      • View Item
      •   UMY Repository
      • 03. DISSERTATIONS AND THESIS
      • Students
      • Undergraduate Thesis
      • Faculty of Engineering
      • Department of Electrical Engineering
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      ANALISIS PRAKIRAAN BEBAN PUNCAK PADA GARDU INDUK WATES DENGAN METODE JARINGAN SYARAF TIRUAN BACKPROPAGATION

      Thumbnail
      View/Open
      COVER (170.7Kb)
      HALAMAN JUDUL (849.9Kb)
      HALAMAN PENGESAHAN (693.1Kb)
      ABSTRAK (715.9Kb)
      BAB I (840.5Kb)
      BAB II (1.160Mb)
      BAB III (748.6Kb)
      BAB IV (1.689Mb)
      BAB V (820.7Kb)
      DAFTAR PUSTAKA (826.6Kb)
      LAMPIRAN (3.372Mb)
      NASKAH PUBLIKASI (512.7Kb)
      Date
      2019-07-01
      Author
      MARLA, MOHAMAD AZMI
      Metadata
      Show full item record
      Abstract
      The 150KV Wates Substation is the Substation in Kulon Progo district, Wates sub-district which supplies electrical energy in the Kulon Progo area, one of which is supply in the NYIA area (New Yogyakarta International Airport) which is a new airport project which is estimated to require around 20MW of electricity if there is an excess load capacity on the power transformer at the 150KV Wates substation, it will require an estimated peak load in the next few years to prevent this The estimated peak load of the power transformer in the 150KV Wates Substation in the next few years can be predicted using the backpropagation Artificial Neural Network method. Backpropagation Artificial Neural Network is an artificial intelligence system with the ability to learn and gather knowledge of learning outcomes in its cell network (neurons) so as to enable the network as a whole to be more intelligent in responding to input / input given. The ability to learn and accumulate this knowledge allows artificial neural network systems to be able to adapt to the environment that provides input to it. Like the human brain in response to different environmental conditions, the role of ANN in the field of research and development is very important in the future that demands aspects of automation and interactive aspects as well as aspects of speed between tools and humans. The estimated peak load of the power transformer is based on growth in energy consumption and economic growth and population growth while the data used are historical data from 2014 to 2018 which are then processed into input data to estimate the peak load of power transformers at 150KV Wates substations using backpropagation neural network method.
      URI
      http://repository.umy.ac.id/handle/123456789/29048
      Collections
      • Department of Electrical Engineering

      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Theme by 
      @mire NV
       

       

      Browse

      All of UMY RepositoryCollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

      My Account

      Login

      DSpace software copyright © 2002-2015  DuraSpace
      Contact Us | Send Feedback
      Theme by 
      @mire NV