MUHAMAD, KHAIDIRAMSYAH and Fachrurrozi, Muhammad and Arsalan, Osvari (2019) PERBANDINGAN METODE NAÏVE BAYES DENGAN METODE K-NN UNTUK KLASIFIKASI BERITA. Undergraduate thesis, Sriwijaya University.
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Abstract
Berita merupakan informasi yang penting untuk diketahui, banyaknya jenis berita terkadang membuat pembaca menjadi bingung untuk memilih berita apa yang ingin dibaca. salah satu cara untuk memudahkan pembaca memilih berita secara otomatis dan akurat adalah dengan klasifikasi dokumen. Terdapat banyak metode klasifikasi yang dapat digunakan. Penelitian ini menggunakan metode Naive Bayes dan Metode K-Nearest Neighbor, kedua metode ini dipilih karena metode Naïve Bayes adalah klasifikasi berdasarkan probabilitas, metode K-Nearest Neighbor adalah metode pembelajaran berdasarkan jarak terdekat dengan objek tersebut. Klasifikasi ini menggunakan data training sebanyak 1000 data dan data testing sebanyak 100 data. Hasil penelitian menunjukan akurasi K-Nearest Neighbor lebih tinggi dengan K=7 akurasi didapat oleh K-Nearest Neighbor 97% dan Naïve Bayes mendapatkan akurasi sebesar 72%.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | klasifikasi ,metode K-Nearest neighbor (K-NN), metode naive bayes |
Subjects: | Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76 Computer software Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.Z55 Apache Hadoop (Computer file) Electronic data processing--Distributed processing. File organization (Computer science) Data mining. Streaming technology (Telecommunications) |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | Users 707 not found. |
Date Deposited: | 26 Sep 2019 03:15 |
Last Modified: | 26 Sep 2019 03:15 |
URI: | http://repository.unsri.ac.id/id/eprint/8628 |
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