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      •   UMY Repository
      • 03. DISSERTATIONS AND THESIS
      • Students
      • Undergraduate Thesis
      • Faculty of Engineering
      • Department of Information Technology
      • View Item
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      PENERAPAN ALGORITMA C4.5 UNTUK KLASIFIKASI JENIS PEKERJAAN ALUMNI DI UNIVERSITAS MUHAMMADIYAH YOGYAKARTA

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      COVER (197.9Kb)
      HALAMAN JUDUL (652.4Kb)
      HALAMAN PENGESAHAN (345.8Kb)
      ABSTRAK (86.40Kb)
      BAB I (108.7Kb)
      BAB II (289.6Kb)
      BAB III (114.5Kb)
      BAB IV (1.492Mb)
      BAB V (37.59Kb)
      DAFTAR PUSTAKA (97.76Kb)
      LAMPIRAN (2.055Mb)
      NASKAH PUBLIKASI (381.9Kb)
      Date
      2018-08-27
      Author
      RESPATI, BADRAHINI MASAJENG
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      Abstract
      The development of education field in Indonesia comes so fast through all it’s aspects. As for university, one aspect that measure it’s quality is the number of its alumnus that got a job right after they graduate. The purpose of this research is classification the kind of jobs of alumnus of Muhammadiyah University of Yogyakarta to get the factors that effects of their jobs by decision tree using the classification method with C4.5 algorithm. This research methodology begins with conducting library studies, definitive data mining methods, data collection, data selection, data processing, data testing, and making conclusions. This research uses several attributes, among others faculty, year of graduation, GPA, and force as a parameter to classification. And the data is used as many as 259, including 3 Faculty of Economics, Medicine, and the Technical force of 2001-2013 and graduated from 2011-2016. Base on the results, If coming from the faculties of Economics, graduated in 2011 and 2012 the majority of work in Private. If they come from the Faculty of Medicine with the 2011 and 2012 graduation years between 3 to 3.5 majority work in Private, If they come from the majority Engineering faculty working in the private so the most influential attributes for kind of jobs of alumnus faculty as the root of the decision tree and have the highest gain ratio among other attributes. And C4.5 algorithms suitable to be applied on the classification of the type of jobs alumnus.
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      http://repository.umy.ac.id/handle/123456789/22834
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