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"Subdivide and conquer! "Magic search: getting the best results from your catalog and beyond" showcases how to increase the power of Library of Congress Subject Heading (LCSH) subdivisions to produce astonishing results from your searches. Rebecca S. Kornegay and Heidi E. Buchanan, experienced reference librarians, and Hildegard B. Morgan, an expert cataloger, explain how, when used wisely, LCSH subdivisions can save time and provide a new level of precision in information retrieval for patrons of the library. "Magic Search" presents the 467 best-performing LCSH subdivisions that speak to the kinds of research questions librarians handle every day. This quick reference format, along with a handy index, offers a useful tool to keep for quick reference rather than a cumbersome tome to be read from cover to cover. In addition, this book provides: a thematic arrangement of LC subdivisions that yield the most successful search; chapters on discipline-specific subdivisions to hone effective search terms; and, precise, professional vocabulary useful in searches and explained in easy-to-understand language. Grasping the importance and having command of LC subdivisions, now appearing in unexpected places beyond the library catalog, is key in this rapidly evolving, 21st-century information environment. No other work explores the LCSH subdivisions is such detail or with such commitment, making this book vital to every reference desk."

"Peningkatan kunjungan di situs web Online Public Access Catalog (OPAC) Perpustakaan Universitas Indonesia perlu disertai dengan peningkatan kualitas pelayanan, salah satunya melalui penyusunan sistem rekomendasi buku dalam situs web OPAC. Untuk menyusun sistem tersebut, penggalian pola asosiasi antar buku dilakukan dengan menggunakan salah satu metode data mining yaitu association rules. Dua algoritma digunakan yakni algoritma Apriori dan Apriori Inverse. Untuk menguji dan menyeleksi pola yang dihasilkan, objective interestingness measure dilakukan dan menghasilkan sembilan belas pola asosiasi sebagai luaran (output) akhir penelitian.

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An increasing use of Online Public Access Catalog (OPAC) Universitas Indonesia Library's website should be followed by a service quality improvement, such as organizing a book recommendation system. To build mentioned system, user behaviors in terms of loaned books were discovered by using one of data mining techniques namely association rules. In this research, two algorithms were used which are Apriori and Apriori Inverse. After all association rules were gathered, objective interestingness measure were conducted to evaluate the quality of association rules and resulted nineteen association rules as final output."