PERBANDINGAN ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK MENGKLASIFIKASI PENERIMA BEASISWA BANK INDONESIA SUMATERA SELATAN

PUTRI, INDAH ARSITA and Indah, Dwi Rosa (2024) PERBANDINGAN ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK MENGKLASIFIKASI PENERIMA BEASISWA BANK INDONESIA SUMATERA SELATAN. Undergraduate thesis, Sriwijaya University.

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Abstract

Penelitian ini bertujuan untuk membandingkan kinerja algoritma Decision Tree (C4.5) dan Naïve Bayes dalam mengklasifikasikan penerima beasiswa Bank Indonesia. Metodologi CRISP-DM digunakan pada data 416 record data penerima beasiswa tahun 2023-2024. Evaluasi model dilakukan menggunakan 10-fold cross-validation dan metrik accuracy, precision, recall, serta F-measure. Hasil menunjukkan bahwa Decision Tree (C4.5) memiliki kinerja lebih baik dengan nilai accuracy 82,70%, precision 98%, recall 84,07%, dan F-measure 90,5%, dibandingkan Naïve Bayes dengan accuracy 82,21%, precision 97,43%, recall 83,99%, dan F-measure 90,2%. Meskipun Decision Tree (C4.5) membutuhkan waktu analisis sedikit lebih lama, perbedaannya tidak signifikan.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Data Mining, Klasifikasi
Subjects:	T Technology > T Technology (General) > T58.5-58.64 Information technology > T58.6.E9 Management information systems -- Congresses.
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Indah Arsita Putri
Date Deposited:	10 Jan 2025 07:20
Last Modified:	10 Jan 2025 07:20
URI:	http://repository.unsri.ac.id/id/eprint/163668

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