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All Journal JURNAL MANAJEMEN MOTIVASI Community Engagement and Emergence Journal (CEEJ) Khatulistiwa Law Review Wacana: Jurnal Ilmu Sosial dan Ilmu Politik Interdisiplin Sambulugana Journal of Management, Economic, and Accounting Jurnal Tadris Matematika (JTMT) Jurnal Ekonomi, Manajemen, Bisnis dan Akuntansi Applied Information Technology and Computer Science (AICOMS)
Rahman , Abdul
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Journal : applied information technology and computer science aicoms

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Pemrosesan Query dan Pemeringkatan Judul Berita Terkait Gubernur Jawa Barat Menggunakan TF-IDF dan Cosine Similarity Saputra, Chandra; Wilcent , Wilcent; Irsyad , Hafiz; Rahman , Abdul
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 1 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v4i1.1799

Abstract

Increasing efficiency and relevance in searching for news information is a pressing need in the digital era. This study aims to develop a news title ranking system based on keywords (queries) by combining the Term Frequency-Inverse Document Frequency (TF-IDF) and cosine similarity methods. The data used are 2,507 news titles from four of the most popular news sites in Indonesia, namely Kompas.com, Detik.com, CNNIndonesia.com, and Tempo.com in the last one year. The stages carried out include web scraping, pre-processing (case folding, tokenizing, stopwords removal, and stemming), word weighting using TF-IDF, similarity calculation using cosine similarity, to system performance evaluation with accuracy, precision, recall, and f1-score metrics. The test results on three different queries show that the system is able to provide very good results with an average accuracy of 99.75%, precision 96.67%, recall 100%, and f1-score 98.33%. This study shows that the combination of TF-IDF and cosine similarity is effective in optimizing the search for news titles that are relevant to the entered query.
Pemrosesan Query dan Pemeringkatan Judul Berita Terkait Gubernur Jawa Barat Menggunakan TF-IDF dan Cosine Similarity Saputra, Chandra; Wilcent , Wilcent; Irsyad , Hafiz; Rahman , Abdul
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 1 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/aicoms.v4i1.1799

Abstract

Increasing efficiency and relevance in searching for news information is a pressing need in the digital era. This study aims to develop a news title ranking system based on keywords (queries) by combining the Term Frequency-Inverse Document Frequency (TF-IDF) and cosine similarity methods. The data used are 2,507 news titles from four of the most popular news sites in Indonesia, namely Kompas.com, Detik.com, CNNIndonesia.com, and Tempo.com in the last one year. The stages carried out include web scraping, pre-processing (case folding, tokenizing, stopwords removal, and stemming), word weighting using TF-IDF, similarity calculation using cosine similarity, to system performance evaluation with accuracy, precision, recall, and f1-score metrics. The test results on three different queries show that the system is able to provide very good results with an average accuracy of 99.75%, precision 96.67%, recall 100%, and f1-score 98.33%. This study shows that the combination of TF-IDF and cosine similarity is effective in optimizing the search for news titles that are relevant to the entered query.
Co-Authors Abdullah , Sait Abdullah, Sait Ade Irawan, Muhammad Afandi , Muhamad Nur Ali Sunarno Angriani , Ida Apriandi, Seldy Aprizal Aprizal Asdar Dollo Chandra Saputra Dewi Kunia Efendi, Sekuan Eli Karliani Endarwati, Eris Fernanda Fajeri, Mochammad Firdaus Achmad Hanila , Siti Henra Ahmad Ibrahim , Risfandi Ida Anggriani Irsyad , Hafiz Latifa, Latifa Listiani , Teni Muhammad Irfan Muliadi Pransiska, Anita Putri Utami, Aisyah R Siagian, Enika Salsabila Samsuria, Samsuria Saputri, Rahma Silmi, Muhammad Andhika Siregar , Zulli Umri Susanti , Neri Wilcent , Wilcent