Klasifikasi Kemacetan Lalu Lintas Kota Malang Melalui Media Twitter Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NW-KNN) - Putu Amelia Vennanda Widyaswari; Indriati Indriati; Rizal Setya Perdana (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Twitter is a social media that is still widely used today. Like other social media Twitter is useful for making friends, exxchanging messages, and information about various things such as entertainment, economy, politics, and so forth. Twitter is also useful for finding information about the state of traffic on a road by accessing traffic accounts on Twitter. However, tweets are often found with ambigous words about the condition of the road. So tweets needs to classified to make it easy for road users. Classification begins with doing preprocessing stages on training and test documents, then proceeding with weighting TF-IDF until the classification stage using the NW-KNN (Neighbor Weighted K-Nearest Neighbor) method. Based on the implementation and testing carried out on the study of Malang City Traffic Congestion Classification Through Media Twitter Using Neighbor Weighted K-Nearest Neighbor (NW-KNN) method which uses 600 training data and 150 test data, obtained results of 0.7336507 for the average precision, 0.2210526 for recall, 0.3002686 for f-measure, and accuracy obtained at 0.665.