<![CDATA[News through television media is still one of the media that is widely used by the public in obtaining the latest information. The Central Java TVRI Public Broadcasting Institution has a news program called Berita Jawa Tengah which airs every day and doesn’t have a classification system. This research was carried out in several stages, in the initial stage preprocessing was carried out which included: data collection, cleaning, case folding, tokenizing, normalization, stopword removal, stemming, then continued with word weighting (TF-IDF) and finally applying the K-Nearest Neighbor classification method (K-NN), Naïve Bayes and Support Vector Machine (SVM). The results of the classification carried out show that the K-NN classification method has higher results compared to other methods, namely an Accuracy value of 0.94, Precision 0.92, Recall 0.94 and f1-score 0.93, so it can be concluded that Television news classification using the K-NN method is the method that provides the most accurate results.]]>
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