Search Of Favorite Books As A Visitor Recommendation of The Fmipa Library Using CT-Pro Algorithm

Sufiatul Maryana, Lita Karlitasari

Abstract


The library of Faculty of Mathematics and Natural Science (FMIPA) has a collection of books and other print media, total of 2,678 books with 7237 visitors and 2148 borrowers. The available book search system was very helpful for visitors to find the required books. Especially if the system has features recommended of books. In the provision of book recommendations used one of the data mining techniques, namely association rule mining techniques or excavation of association rules. In the development of this recommendation system, KDD (Knowledge Discovery from Database) model was used. The data used was the transaction history of borrowing book with the category of "chemistry", for the last 5 (five) months, that is September 2014 - February 2015. The excavation technique of this association rule has 2 (two) main process, they are: frequent patterns and rules. To find frequent patterns, a CT-PRO algorithm was used. The minimum value of support used was 1 and 2. Once the pattern is found, the confidence value of each pattern was calculated. The minimum value of confidence used ranges from 10% to 100%. The recommendation rule was based on calculating the value of this confidence. The comparison of minimum support values indicates that the greater value of minimum support then the less borrowing pattern was generated, and vice versa. The comparison of minimum confidence value shows that the greater of minimum confidence value then the less recommended rule given..


Keywords: Library, Recommended System, Knowledge Discovery from Database (KDD), Association Rule Mining, CT-PRO Algorithm


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References


Ahlemeyer-Stubbe, Andrea. Coleman, Shirley. 2014. A Practical Guide to Data Mining for Business and Industry. WILEY, United Kingdom.

Bell, Jason. 2015. Machine Learning: Hands-On for Developers and Technical Professionals. John Wiley & Sons, Inc, Indiana Polis, Canada.

Brown, Meta S. 2014. Data Mining For Dummies. John Wiley & Sons, Inc, New Jersey, Canada.

Dwi Maryati, Sri Setyaningsih, Lita Karlitasari. Penerapan metode association rule mining untuk rekomendasi penelusuran buku dengan menggunakan algoritma CT-PRO. Skripsi, FMIPA, Universitas Pakuan. 2015

Gupta, Bharat. 2011. FP-Tree Based Algorithms Analysis: FPGrowth, COFI-Tree and CT-PRO. International Journal on Computer Science and Engineering (IJCSE). 3 : 2691 – 2699.

Han, Jiawei. Kamber, Micheline. Pei, Jian. 2012. Data Mining Concepts and Techniques 3rd Edition. Morgan Kaufmann, USA.

Harrington, Peter. 2012. Machine Learning in Action. Manning, Shelter Island, New York.

Sucahyo, Yudho Giri. Gopalan, Raj. P. 2004. CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure.

Wandi, Nugroho. Hendrawan, Rully A. Mukhlason, Ahmad. 2012. Pengembangan Sistem Rekomendasi Penelusuran Buku dg Penggalian Association Rule Menggunakan Algoritma Apriori. Jurnal Teknik Institut Teknologi Sepuluh November (ITS). 1 : A445 – A449.


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