• DocumentCode
    3580817
  • Title

    Model prediction for accreditation of public junior high school in Bogor using spatial decision tree

  • Author

    Giri, Endang Purnama ; Arymurthy, Aniati Murni

  • Author_Institution
    Fac. of Comput. Sci., Univ. of Indonesia, Depok, Indonesia
  • fYear
    2014
  • Firstpage
    333
  • Lastpage
    338
  • Abstract
    Indonesia has a large geographic area with large variance of quality service of education. This paper will analyze whether it has a correlation or not, between the quality level of school and its characteristic of geographic area. This paper describes performance of two kind of decision tree method in predicting level of accreditation for public junior high school in Bogor, West Java. With three scenarios (training set as testing set, leave one out, and 3-fold cross validation) using conventional decision tree (ID3) the accuracy level reach 97.14%, 40%, and 51.51% respectively. On the other hand, using spatial decision tree (SDT) the accuracy reach level 97.14%, 54.29%, and 54.28%. Based on the accuracy level and the structure of tree that was constructed, SDT produce better result. These facts will imply that quality level of public junior high schools on Bogor have correlation with characteristics of geographic area. However, SDT need much more computation time to construct decision tree rather than ID3, so for big number of data and big number of attributes, SDT will not appropriate.
  • Keywords
    decision trees; educational institutions; geographic information systems; Bogor public junior high school accreditation; ID3; SDT; West Java; education; model prediction; spatial decision tree method; Accreditation; Accuracy; Decision trees; Entropy; Feature extraction; Java; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Science and Information Systems (ICACSIS), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICACSIS.2014.7065831
  • Filename
    7065831