View Item 
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Statistics and Data Sciences
      • View Item
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Statistics and Data Sciences
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Pendugaan Nilai Ekstrim Menggunakan Sebaran Champemowne Termodifikasi, Sebaran Pareto Terampat, dan Nilai Gabungan (Studi Kasus Curah Hujan Harian Darmaga Bogor)

      Thumbnail
      View/Open
      full text (1.334Mb)
      Date
      2013
      Author
      Hafid, Muhammad
      Wigena, Aji Hamim
      Djuraidah, Anik
      Metadata
      Show full item record
      Abstract
      Extreme rainfall can give a negative affect for human activity. Negative effect of production failure in agriculture and plantations can be anticipated by extreme rainfall estimation that may occur in the future. The aims of this study is to compare the extreme rainfall estimation using the modified Champernowne distribution and generalized Pareto distribution (GPD), and determine the optimum weights of combined extereme value estimation. Modified Champernowne distribution patern has convergence to the GPD that the distribution function consists of three parameters that describe the data center, the diversity, and characteristics of the end of the distribution. While GPD consists of two parameters that describe the diversity and characteristics of the end of the distribution (heavy tail/tail light). The data used are daily rainfall data in Darmaga Bogor Station during the period 1985-June 2011 were obtained from the Indonesian Agency for Meteorology Climatology and Geophysics. GPD estimation tends to over estimate while modified Champernowne distribution estimation tends to under estimate. The combine of the estimated value by weighted produces more accurate extreme value estimation. Forecasting results for 1, 2, and 3 month ahead show that the best prediction based on modified Champernowne distribution, while forecasting results for 6 and 9 month ahead is very well predicted by GPD and combined value.
      URI
      http://repository.ipb.ac.id/handle/123456789/65865
      Collections
      • UT - Statistics and Data Sciences [1212]

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository
        

       

      Browse

      All of IPB RepositoryCollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

      My Account

      Login

      Application

      google store

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository