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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Andre Rino Prasetyo
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Hoax Pada Berita Kesehatan Berbahasa Indonesia Dengan Menggunakan Metode Modified K-Nearest Neighbor Andre Rino Prasetyo; Indriati Indriati; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

News is a source of information about current events which can be found in newspapers, television, the internet and other media. Currently the news that is disseminated often without writing the source clearly, especially the type of news about health, it can lead to misinterpretation because the news is not necessarily true or wrong so it takes a smart system to classify health news is whether included in the category of hoax or fact. The hoax classification process use several stages ranging from preprocessing consisting of tokenisasi and filtering. Continued with word-weighting process and cosine similarity to classification process using Modified K-Nearest Neighbor method. The results obtained based on the implementation and testing resulted in the best value of k amounted to 4, precision of 0,83 recall of 0,75 f-measure of 0,79 and the accuracy of 75%. The test results obtained because the health news content used is still too common, many non-standard words and the determination of k-values ​​used are very influential on whether or not the process of classification of health news documents.
Co-Authors Indriati Indriati Putra Pandu Adikara