Deteksi Clickbait dengan Sentence Scoring Based On Frequency di Detik.Com

Budi Wijaya Rauf; Suwanto Raharjo; Heri Sismoro

doi:10.36294/jurti.v4i2.1381

Deteksi Clickbait dengan Sentence Scoring Based On Frequency di Detik.Com

Budi Wijaya Rauf, Suwanto Raharjo, Heri Sismoro

Abstract

Abstract - The clickbait phenomenon has become one of the powerful ways to increase the number of readers for a website. With the increasing number of visitors to the site, the higher the income on the website. However, this clickbait technique is like a double-edged knife. Many people who do not like this technique because of incompatibility of the title and content of the article being read. This study aims to detect clickbait articles on the Indonesian news site detik.com by using python and sentence scoring based on frequency algorithms to find a match between the title and content of the article. Appropriate titles and contents will be given a value of 1 (one) and those that are not appropriate will be given a value of 0 (zero), the results of the test system are compared with existing datasets and produce an accuracy rate of 75%, 57% precision and 80% recall.

Keywords - Clickbait Detection, Sentence Scoring Based on Frequency, Python.

Abstrak – Fenomena clickbait sudah menjadi salah satu cara ampuh untuk meningkatkan jumlah pembaca untuk sebuah website. Dengan meningkatnya jumlah pengunjung pada situs maka semakin tinggi pula pendapatan pada website tersebut. Namun, Teknik clickbait ini seperti pisau bermata dua. Banyak masyarakat yang tidak suka dengan Teknik ini dikarenakan ketidaksesuaian judul dan isi artikel yang dibaca. Penelitian ini bertujuan untuk mendeteksi artikel clickbait pada situs berita Indonesia detik.com dengan menggunakan python dan algoritma sentence scoring based on frequency guna mencari kecocokan antara judul dan isi dari artikel tersebut. Judul dan isi yang sesuai akan diberikan nilai 1 (satu) dan yang tidak sesuai akan diberikan nilai 0 (nol), hasil uji coba system tersebut dibandingkan dengan dataset yang telah ada dan menghasilkan tingkat akurasi sebesar 75%, presisi 57% dan recall 80%.

Kata Kunci - Deteksi Clickbait, Sentence Scoring Based on Frequency, Python.

Keywords

Deteksi Clickbait; Sentence Scoring Based on Frequency; Python

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References

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DOI: https://doi.org/10.36294/jurti.v4i2.1381