Pola peminjaman buku di perpustakaan Universitas Syiah Kuala menggunakan Algoritma Eclat

https://doi.org/10.22146/bip.32089

Muhammad Subianto(1*), Fitriana AR(2), Meildha Hijriyana P.(3)

(1) Jurusan Informatika, FMIPA Universitas Syiah Kuala, Banda Aceh
(2) Jurusan Informatika, FMIPA Universitas Syiah Kuala, Banda Aceh
(3) Jurusan Informatika, FMIPA Universitas Syiah Kuala, Banda Aceh
(*) Corresponding Author

Abstract


Introduction. UPT Unsyiah Library is one of the facilities in Syiah Kuala University which provides book lending service to users.The library collects all information and has expanded a big data of book lending.

Data Collection Method. This research aims to determine the relevance pattern between the book subject and the borrower's program of study, and to determine the pattern of book borrowing based on books that are often borrowed simultaneously. The pattern can be found using one of the methods of data mining that is the association rules mining with Eclat algorithm. Eclat algorithm uses vertical format of dataset to intersect TID list between items in determining support count so that the process of searching frequent itemset is faster.

Analysis Data. There are 122.945 book lending data from 2007 to 2015 used in this study. These data show the borrowers’ behavior pattern of book lending behavior in UPT Library Unsyiah, especially the borrowers who are student of this university. Results and Discussions. The Eclat algorithm produces the most frequent and repeatable pattern of book subjects and program of studies from several years of research data, which are Accounting book subjects with its program of study (S1) and Chemistry book subjects with Chemistry Education program of study (S1).

Conclusions. The analysis result for the book subject pattern and program of studies shows that the habit of Unsyiah students in borrowing books from the library is accordingly to their program of studies. As for the patterns between books, Eclat algorithm found linkage between books and most often repeated from several periods of years of research data is the book code of 12311 (Fundamentals of educational evaluation) with 42265 (Introduction to evaluation of education).


Keywords


Association rules mining; Eclat; Library

Full Text:

PDF


References

Aprilina, M. N. Q., Wiranto, & Widodo. (2015). Analisa Konsistensi Pola Peminjaman Buku Menggunakan Algoritma FP-Groth. In M. A. Muslim, A. Purwinarko, F. A. Setyawan, B. Prasetiyo, A. T. Putra, E. Listiana,  U. I. Larasati (Eds.), Seminar Nasional Ilmu Komputer (SNIK 2015) (pp. 227–234). Semarang, 10 Oktober 2015.

Azwar, A. (2014). Analisa Pola Peminjaman Buku Perpustakaan Menggunakan Algoritma Apriori. Jurnal Edik Informatika, Vol 1, No, 52–62.

Borgelt, C. (2003). Efficient Implementations of Apriori and Eclat. In Proc. 1st IEEE ICDM Workshop on Frequent Item Set Mining Implementations (FIMI 2003, Melbourne, FL). CEUR Workshop Proceedings 90 (p. 90).

Hahsler, M., Buchta, C., Gruen, B., & Hornik, K. (2018). arules: Mining Association Rules and Frequent Itemsets. Retrieved from https://cran.r-project.org/package=arules

Han, J., Kamber, M., & Pei, J. (2012). Data Mining Concepts and Techniques (3rd ed.). Morgan Kaufmann.

Kaur, M., & Grag, U. (2014). ECLAT Algorithm for Frequent Itemsets Generation. International Journal of Computer Systems, 1(3), 82–84.

Li, J., Liu, Y., Liao, W., & Choudhary, A. (2006). Parallel Data Mining Algorithms for Association Rules and Clustering.

Olson, D. L., & Delen, D. (2008). Advanced Data Mining Techniques (1st ed.). Springer Publishing Company, Incorporated.

Omiecinski, E. R. (2003). Alternative Interest Measures for Mining Associations in Databases. IEEE Transactions on Knowledge and Data Engineering, 15(1), 57–69. https://doi.org/http://doi.ieeecomputersociety.org/10.1109/TKDE.2003.1161582

R Core Team. (2017). R: A Language and Environment for Statistical Computing. Vienna, Austria. Retrieved from https://www.r-project.org/

Renstra UPT. Perpustakaan Unsyiah. (2014). Dokumen Rencana Strategis (Renstra) 2015-2018 UPT. Perpustakaan Unsyiah. UPT. Perpustakaan Unsyiah. Banda Aceh.

Rodin, R. (2015). Urgensi Kualitas Pelayanan Perpustakaan Perguruan Tinggi. Al-Kuttab : Jurnal Perpustakaan Dan Informasi, 2(1), 1–20. Retrieved from http://e-journal.perpustakaanstainpsp.net/index.php/alkuttab/article/view/49

Slimani, T., & Lazzez, A. (2014). Efficient Analysis of Pattern and Association Rule Mining Approaches. International Journal of Information Technology and Computer Science, 6(3), 70–81. Retrieved from http://arxiv.org/abs/1402.2892

Supardi, Ratnawati, D. E., & Mahmudy, W. F. (2014). Pengenalan pola transaksi sirkulasi buku pada database perpustakaan menggunakan algoritma generalized sequential pattern. Jurnal Mahasiswa PTIIK Universitas Brawijaya, 4(11), 1–8.

Wandi, N., Hendrawan, R. A., & Mukhlason, A. (2012). Pengembangan Sistem Rekomendasi Penelusuran Buku dengan Penggalian Association Rule Menggunakan Algoritma Apriori (Studi Kasus Badan Perpustakaan dan Kearsipan Provinsi Jawa Timur). Jurnal Teknik ITS, 1(Sept, 2012), 445–449.

Zaki, M. J., Parthasarathy, S., Ogihara, M., & Li, W. (1997). New Algorithms for Fast Discovery of Association Rules. In Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (pp. 283–286). AAAI Press. Retrieved from http://dl.acm.org/citation.cfm?id=3001392.3001454



DOI: https://doi.org/10.22146/bip.32089

Article Metrics

Abstract views : 749 | views : 347

Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 Berkala Ilmu Perpustakaan dan Informasi

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

Currently, Berkala Ilmu Perpustakaan dan Informasi indexed by:

 
ROAD CORE