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

Penulis

  • Lisna zahrotun Universitas Ahmad Dahlan - UAD
  • Tedy Setiadi Universitas Ahmad Dahlan
  • Taufik Mufti Haryadi

DOI:

https://doi.org/10.25077/TEKNOSI.v4i1.2018.37-43

Abstrak

A tracer study is an approach that allows higher education institutions to obtain information about possible deficiencies during educational process and learning process and activity planning for improvement. Institute of Student Affairs never do a tracer study data analysis, although tracking of graduate student has been periodically using web-based application but the previous data is still in old format. Tracer study process is only once time in order to completed   accreditation requirement for department. In this research we will focus in developing the application using FOLDARM method for student tracer study. Application is created using the CI Framework programming language with   Mysql as backend database. The test is done using lift ratio method. The result show, association of the patterns are counted by 3, 24% support and confident 45% and it that meet the criteria. By using lift ratio test, the pattern that has the strongest relationship is if the waiting period in finding a job is 3- 5,9 month and first salary is below Rp. 1,572,200,-  and IPK is between 2.75 - 3.50 and graduation age is between 15-24 years old.

Biografi Penulis

Lisna zahrotun, Universitas Ahmad Dahlan - UAD

Dosen Teknik Informatika

Referensi

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.

Unduhan

Telah diserahkan

18-07-2017

Diterima

17-01-2018

Diterbitkan

01-05-2018

Cara Mengutip

[1]
L. zahrotun, T. Setiadi, dan T. M. Haryadi, “Aplikasi Data Mining untuk Mencari Pola Asosiasi Tracer Study Menggunakan Algoritma FOLDARM”, TEKNOSI, vol. 4, no. 1, hlm. 37–43, Mei 2018.

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