Penerapan Algoritma C4.5 untuk Klasifikasi Jenis Pekerjaan Alumni di Universitas Muhammadiyah Yogyakarta

Authors

  • Asroni Asroni Universitas Muhammadiyah Yogyakarta
  • Badrahini Masajeng Respati Universitas Muhammadiyah Yogyakarta
  • Slamet Riyadi Universitas Muhammadiyah Yogyakarta

DOI:

https://doi.org/10.18196/st.212222

Keywords:

Algoritma C4.5, Gain ratio, Pohon keputusan, Data mining, Alumni

Abstract

The development of education in Indonesia has increased very rapidly. One of the things that have become a benchmark for success in the quality of education at the university is the kind of job getting graduates after graduation. This research aims to identify factors that have an impact on the type of job classification method based on the C 4.5 alumni algorithm. The methodology of this research begins with the study of literature, the identification of a process of data extraction, data selection, data collection, data processing, data testing, and DA conclusion. This research uses some features of the data on a few faculty members, the year of graduation, the annual completion rate, and the strength as a classification performance parameter. Graduates data used up to 259, and consisted of 3 faculties of Economics, medicine and engineering forces from 2001-2013 and graduated from 2011-2016. The research results that have been done is if it comes from the Faculty of Economics, in 2011 and 2012 the majority of work in the private sector has passed, if it comes from the Faculty of Medicine with the years 2011 and 2012 graduated with a cumulative labor rate of between 3 to 3.5 majority working in The private sector, 2012 with a GPA between 3 and 3.5 working in the Private Sector. Finally, the C4.5 algorithm is suitable for the classification of alumni work types.

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Published

2018-12-13

How to Cite

Asroni, A., Respati, B. M., & Riyadi, S. (2018). Penerapan Algoritma C4.5 untuk Klasifikasi Jenis Pekerjaan Alumni di Universitas Muhammadiyah Yogyakarta. Semesta Teknika, 21(2), 158–165. https://doi.org/10.18196/st.212222

Issue

Vol. 21 No. 2 (2018): NOVEMBER 2018

Section

Articles

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