IMPLEMENTASI ALGORITMA APRIORI UNTUK MENENTUKAN POLA REKOMENDASI PEMINJAMAN BUKU DI PERPUSTAKAAN

ERWANSYAH, ANDI (2024) IMPLEMENTASI ALGORITMA APRIORI UNTUK MENENTUKAN POLA REKOMENDASI PEMINJAMAN BUKU DI PERPUSTAKAAN. S1 thesis, Universitas Mercu Buana - Menteng.

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Abstract

Perpustakaan merupakan tempat penyimpanan koleksi buku yang meliputi beragam disiplin ilmu, diorganisir secara teratur, dan berfungsi sebagai sumber informasi. Setiap informasi peminjaman buku disimpan oleh perpustakaan sehingga menghasilkan data peminjaman buku dalam ukuran besar yang dapat menyebabkan masalah di kemudian hari. Untuk mengatasi hal ini, peneliti menggunakan algoritma apriori dan Aplikasi Jupyter yang menggunakan bahasa pyton untuk mengolah data peminjaman buku perpustakaan pada Universitas mercubuana, berdasarkan metode association rule agar dapat mengetahui nilai support,confidence, dan lift ratio. Dari hasil penelitian ini menunjukkan buku yang sering dipinjam bersamaan dengan minimum support 0,5, confidence 90% dan lift ratio 70% adalah Auditing dan pelayanan verifikasi pendekatan terpadu, Advanced Accounting, Jasa Audit Dan Assurance Pendekatan Terpadu (Adaptasi Indonesia). dengan minimum support 0.0051, confidence 1.0, dan lift ratio 195. Hasil ini dapat dijadikan rujukan bagi pihak perpustakaan Universitas Mercubuana dalam menentukan pola rekomendasi peminjaman buku. A library is a storage place for book collections covering various scientific disciplines, organized regularly, and functions as a source of information. Every book borrowing information is stored by the library, resulting in large book borrowing data which can cause problems in the future. To overcome this, researchers used an a priori algorithm and the Jupyter application which uses the Python language to process library book borrowing data at Mercubuana University, based on the association rule method in order to find out the support, confidence and lift ratio values. From the results of this research, it shows that the books that are often borrowed together with a minimum support of 0,5%, confidence of 90% and a lift ratio of 70% are Auditing and integrated approach verification services, Advanced Accounting, Integrated Approach Audit and Assurance Services (Indonesian Adaptation). with minimum support of 0.005, confidence of 1.0, and lift ratio of 195. These results can be used as a reference for the Mercu Buana University library in determining book borrowing recommendation patterns.

Item Type: Thesis (S1)
NIM/NIDN Creators: 41519120119
Uncontrolled Keywords: Perpustakaan, Peminjaman Buku , Algoritma Apriori, Association Rule Libraries, Book Lending, Apriori Algorithms, Association Rules
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: SILMI KAFFA MARISKA
Date Deposited: 06 Mar 2024 03:20
Last Modified: 06 Mar 2024 03:20
URI: http://repository.mercubuana.ac.id/id/eprint/86825

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