Literature Review Klasifikasi Data Menggunakan Metode Cosine Similarity dan Artificial Neural Network - Meilina, Lely; Kumara, I Nyoman Satya; Setiawan, I Nyoman (Majalah Ilmiah Teknologi Elektro; Vol 20 No 2 (2021): (Juli-Desember) Majalah Ilmiah Teknologi Elektro, 2021)
One of the positive impacts arising from technological developments is the ease in conveying aspirations and in obtaining information very quickly. The benefits of this technological development can be felt by all sectors, including the government sector which must protect the people and the state. In improving the quality of public services, the government must implement a government based on digital information technology. Therefore, the central and regional governments have provided online-based public complaint services. To improve the quality of service, the online complaint system must run optimally. The methods that are widely used to find the similarity of the complaint text are the cosine similarity method and the Artificial Neural Network (ANN) method for classifying complaint data. This study reviews the application of the two methods to determine the level of accuracy before it can be implemented in the online complaint system. The results of the review state that the Cosine Similarity method has an accuracy rate of 71.5% and ANN has an accuracy rate of 77%. While other method have an accuracy rate of 67%. From the percentage of this values, its can be concluded use of  Cosine Similarity and ANN methods is feasible to use in classifying data in the Online Community Complaint System.