Kreator konten menggunakan clickbait sebagai cara untuk menarik pengunjung di Youtube. Penelitian ini terkait judul konten Youtube yang bersifat clickbait. Penelitian ini bertujuan untuk menampilkan hasil deteksi judul konten Youtube disesuaikan dengan data pembelajaran dari responden. Metode yang digunakan pada penelitian ini adalah text mining, backpropagation. Text mining untuk melakukan preprocessing teks, term frequency – inverse document frequency dan ekstraksi teks. Preprocessing teks meliputi casefolding, tokenizing, filtering dan stemming. Term frequency – inverse document frequency meliputi pembobotan term frequency(tf), document frequency(df), inverse document frequency(idf), and weighting document term(wdt). Ekstraksi teks terdiri dari positive keyword dan bobot koneksi antar kalimat. Sedangkan backpropagation untuk mendeteksi hasil keluaran dengan nilai target. Berdasarkan hasil pengujian dengan 353 data judul konten Youtube yang dilakukan, backpropagation memiliki nilai precision sebesar 43% dan nilai recall sebesar 42%.

Content creators use clickbait as a way to attract visitors on Youtube. This research is related to the title of Youtube content which is clickbait. This study aims to display the results of the detection of YouTube content titles adapted to the learning data from respondents. The metContent creators use clickbait as a way to attract visitors on Youtube. This research is related to the title of Youtube clickbait content which is clickbait. This study aims to display the results of the detection of YouTube content titles adapted to the learning data from respondents. The method used in this research is text mining, backpropagation. Text mining for preprocessing text, term frequency-inverse document frequency, and text extraction. Text preprocessing includes case-folding, tokenizing, filtering and stemming. Term frequency-inverse document frequency includes weighting term frequency, document frequency, inverse document frequency, and weighting document term. Text extraction consists of positive keywords and the weight of the connection between sentences. While backpropagation is to detect output with target values. Based on the results of testing with 353 Youtube content title data conducted, backpropagation has a precision value of 43% and a recall value of 42%.