Aplikasi Data Mining untuk Mencari Pola Asosiasi Tracer Study Menggunakan Algoritma FOLDARM

Lisna zahrotun, Tedy Setiadi, Taufik Mufti Haryadi


The Tracer Study is an approach that allows higher education institutions to obtain information about possible deficiencies in the educational process and learning process and can for planning activities for future improvement. In the Institute of Student Affairs has never done tracer study data analysis, although the tracking of graduate data has been periodic and web-based but some data is still stored in the form of excel. During this tracer study process is only done on each study program at the time will make the submission of accreditation.

In this research will focus on making the application of association pattern with FOLDARM method in tracer study. The program is created using the CI Framework programming language and uses the mysql php database. The test is done using the lift ratio method.

In this research, the association patterns that meet the above criteria are counted 3, 24% support and confident 45%. By using the test using lift ratio, the pattern that has the strongest relationship is if the waiting period is looking for work 3- 5,9 month and salary first work Salary <1,572,200 and value of IPK 2.75 - 3.50 and age when pass For Age 15-24 years then Graduation is not on time

Teks Lengkap:



Renny, R. Candra, S. Ruhama, and M. W. SArjono, “Exploring Tracer Study Service in Career Center Web Site of Indonesia higher Education,” Int. Comput. Sience Informaion Secur., vol. 11, pp. 36–39, 2013.

M. Abidin, “Alumni Satisfaction on Curriculum Structure And Learning Process in Indonesian Islamic University,” Int. J. Sci. Res. Educ., vol. 3, no. 2, pp. 2900–2905, 2015.

H. Yuliansyah and L. Zahrotun, “Designing web-based data mining applications to analyze the association rules tracer study at university using a FOLD-growth method,” Int. J. Adnvanced Comput. Res., vol. 6, no. 27, pp. 215–221, 2016.

S. M. P, Y. H. Yadi, and W. Susihono, “Evaluasi Tracer Study Untuk Pembelajaran dengan Pendekatan Ergonomi Makro,” J. Tek. Ind., vol. 1, no. 4, pp. 284–288, 2013.

Y. wong Woon, W. K. Ng, and A. Das, “Fast online dynamic association rule mining,” in In proceedings of the second international conference on web information systems engineering., 2001, pp. 278–287.

B. Santosa, Data Mining Teknik Pemanfaatan Data untuk Keperluan Bisnis. Yogyakarta: Graha Ilmu, 2007.

S. Susanto and D. Suryadi, Introduction to data mining gain knowledge of a chunk of data. Yogyakarta: CV ANDI OFFSET., 2010.

R. Soelaiman and M. N. Arini, “Analisis Kinerja Algoritma Fold-Growth dan Fp-growth pada Penggalian Pola Asosiasi,” SNATI (Seminar Nas. Apl. Teknol. Informasi), vol. 2006, pp. 13–18, 2006.

J. Han and M. Kamber, Data Mining Concepts and Techniques. San Diego: Morgan Kaufmann, 2001. [10] B. Akreditasi and N. Perguruan, “Standar dan Prosedur Akreditasi Institusi Perguruan Tinggi,” 2007.

W. Purwaningseh, “Analisis Pencari Kerja Menurut Kelompok Umur, Tingkat Pendidikan, dan Golongan Pokok Jabatan di Kabupaten Kudus,” 2010.

Artikel Statistik

Abstrak telah dilihat : 47 kali
PDF telah dilihat : 27 kali


  • Saat ini tidak ada refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Alamat Redaksi :
Jurusan Sistem Informasi, Fakultas Teknologi Informasi
Universitas Andalas
Kampus Limau Manis, Padang 25163, Sumatera Barat

email: teknosi@fti.unand.ac.id

  Jumlah Pengunjung :


Creative Commons License
This work by si.fti.unand.ac.id is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.