ANALISIS POLA PEMINJAMAN BUKU PADA SISTEM PERPUSTAKAAN DIGITAL MENGGUNAKAN ALGORITMA FP-GROWTH DAN TEKNIK PRUNING
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Abstract
Manajemen perpustakaan menghadapi tantangan dalam pengelolaan data sirkulasi yang semakin kompleks akibat peningkatan literasi digital dan kebutuhan informasi yang terus berkembang. Penelitian ini bertujuan untuk menganalisis pola peminjaman buku di UPT Perpustakaan Universitas Latansa Mashiro dengan menerapkan algoritma Frequent Pattern Growth (FP-Growth) yang dioptimalkan melalui teknik pruning. Proses analisis dilakukan menggunakan perangkat lunak RapidMiner versi 9.10, dengan dataset terdiri dari 1.012 transaksi peminjaman buku selama periode Januari–Juni 2025. FP-Growth digunakan untuk mengekstraksi pola asosiasi antar itemset secara efisien tanpa proses pencarian kandidat, sedangkan pruning berfungsi untuk menghapus item dengan frekuensi rendah guna meningkatkan presisi hasil. Hasil eksperimen menunjukkan adanya korelasi kuat antara buku Manajemen dan Ekonomi (support 27%, confidence 54%, lift 956) yang meningkat menjadi (support 27%, confidence 64%, lift 1.233) setelah pruning diterapkan. Jumlah aturan asosiasi juga menurun dari 26 menjadi 8, namun dengan peningkatan kekuatan korelasi dan relevansi. Evaluasi visual dilakukan melalui perbandingan treemap dan confusion matrix-based validation untuk mengukur efektivitas aturan. Penelitian ini memiliki kontribusi baru dalam penerapan teknik pruning pada algoritma FP-Growth di konteks perpustakaan digital, yang masih jarang dieksplorasi dalam literatur. Temuan ini berimplikasi penting bagi pengambilan keputusan strategis dalam pengadaan koleksi, penataan layout rak, dan pengembangan sistem rekomendasi berbasis sirkulasi di lingkungan perpustakaan.
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