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

Asroni Asroni, Badrahini Masajeng Respati, Slamet Riyadi

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.


Keywords


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

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References


Andriani, Anik. (2012). Penerapan Algoritma C4. 5 Pada Program Klasifikasi Mahasiswa Dropout. In , 139–47.

Elisa, Erlin. (2017). Analisa dan Penerapan Algoritma C4.5 Dalam Data Mining Untuk Mengidentifikasi Faktor-Faktor Penyebab Kecelakaan Kerja Kontruksi PT.Arupadhatu Adisesanti. Jurnal Online Informatika 2 (1): 36–41.

Fansuri, Farid. (2012). Jurnal Komputer dan Informatika (KOMPUTA). 1: 5.

Ginting, Selvia Lorena Br, Wendi Zarman, and Ida Hamidah. (2014). Analisis Dan Penerapan Algoritma C4. 5 Dalam Data Mining Untuk Memprediksi Masa Studi Mahasiswa Berdasarkan Data Nilai Akademik. No. November.

Kamagi, David Hartanto, and Seng Hansun. (2014). Implementasi Data Mining Dengan Algoritma C4. 5 Untuk Memprediksi Tingkat Kelulusan Mahasiswa. Vol. VI, no. 1: 15–20.

Mabrur, Angga Ginanjar. (2012). Penerapan Data Mining Untuk Memprediksi Kriteria Nasabah Kredit. Komputa: Jurnal Ilmiah Komputer Dan Informatika 1 (1).

Nugroho, Yusuf Sulistyo. (2014). Penerapan Algoritma C4. 5 Untuk

Klasifikasi Predikat Kelulusan Mahasiswa Fakultas Komunikasi Dan Informatika Universitas Muhammadiyah Surakarta. In , A1–6.

Santoso, Teguh Budi. (n.d). Analisa Dan Penerapan Metode C4.5 Untuk Prediksi Loyalitas Pelanggan. 10: 10.

Sembiring, Muhammad Ardiansyah, Mustika Fitri Larasati Sibuea, and Andy Sapta. (n.d). Analisa Kinerja Algoritma C.45 Dalam Memprediksi Hasil Belajar, 7.

Widayu, Hikma, Surya Darma Nasution, Natalia Silalahi, and Mesran Mesran. (2017). Data Mining Untuk Memprediksi Jenis Transaksi Nasabah Pada Koperasi Simpan Pinjam Dengan Algoritma C4. 5. Media Informatika Budidarma 1 (2).




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

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