KOMPARASI ALGORITMA SUPPORT VERTOR MACHINE DAN NA�VE BAYES UNTUK DETEKSI JUDUL BERITA CLICKBAIT INDONESIA

FADHILAH, SARAH VINA (2023) KOMPARASI ALGORITMA SUPPORT VERTOR MACHINE DAN NA�VE BAYES UNTUK DETEKSI JUDUL BERITA CLICKBAIT INDONESIA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Many activities can't be separated from the internet, including reading online news. In this era, online news has become a way of life and changed the way people obtain the latest information. With the rise of online news, news makers have become competitive with each other in terms of increasing the ranking of each platform. This has given rise to the emergence of "clickbait" headlines, which are overstated headlines that do not match the content of the news. So, the purpose of this research is to detect clickbait headlines so that people are not instigated by overstated headlines and can avoid and not be affected by exposure to fake news. The methods used in this study are using the Support Vector Machine (SVM) algorithm and the Naïve Bayes algorithm for comparison. The results of this study showed 71% accuracy, 72% precision, 58% recall, and 64% f1 score from using the SVM model and 72% accuracy, 73% precision, 59% recall, and 65% f1 score from using the Naïve Bayes model. Keywords : naïve bayes, SVM, news headline, clickbait Banyak aktivitas yang tidak dapat lepas dari yang namanya internet, termasuk membaca berita online. Di era sekarang ini, berita online dapat dikatakan telah menjadi gaya hidup masyarakat dan mengubah cara masyarakat dalam memperoleh informasi terkini. Semakin maraknya berita online, para pembuat berita menjadi saling bersaing dalam hal meningkatkan peringkat masing-masing platform. Hal itu memunculkan timbulnya judul berita clickbait yaitu judul berita yang dilebih-lebihkan dan tak sesuai dengan isi beritanya. Maka tujuan dari penelitian ini adalah untuk mendeteksi judul berita clickbait agar masyarakat tidak terhasut oleh judul berita yang dilebih-lebihkan serta dapat terhindar dan tidak terpengaruh dari paparan berita bohong. Adapun metode yang dilakukan dalam penelitian ini yaitu menggunakan algoritma Support Vector Machine (SVM) dan algoritma Naïve Bayes untuk perbandingan. Hasil dari penelitian ini memperoleh akurasi 71%, presisi 72%, recall 58%, dan f1 score 64% dari penggunaan model SVM dan akurasi 72%, presisi 73%, recall 59%, dan f1 score 65% dari penggunaan model Naïve Bayes. Kata Kunci : naïve bayes, SVM, judul berita, clickbait

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 23 087
NIM/NIDN Creators: 41519010086
Uncontrolled Keywords: naïve bayes, SVM, judul berita, clickbait
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 > 003 Systems/Sistem-sistem
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 > 003 Systems/Sistem-sistem > 003.5 Computer Modeling and Simulation/Model dan Simulasi Komputer
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: CALVIN PRASETYO
Date Deposited: 22 Sep 2023 01:43
Last Modified: 22 Sep 2023 01:43
URI: http://repository.mercubuana.ac.id/id/eprint/81341

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