Jaringan Syaraf Tiruan LVQ Berbasis Parameter HSV dalam Penentuan Uang Rupiah Palsu - I Gusti Ayu Agung Diatri Indradewi; Made Suci Ariantini (LP2M INSTITUT TEKNOLOGI DAN BISNIS ASIA MALANG, 2019)
ABSTRACT. Counterfeit money when viewed at a glance has the exact same physical with the original money issued by Bank Indonesia. To prevent unintentional transactions using counterfeit money, the government has socialized the 3D method (Visible, Feelable, and Endangered). In addition, in institutions directly related to finance such as banking, as well as on-site shopping have started using a counterfeit money scanner that utilizes ultraviolet light. The lack of this tool requires the accuracy of the human eye to determine genuine or fake money. Determination of authenticity of Rupiah banknotes can be done by using the pattern classification method one of which can be accommodated by artificial neural networks. LVQ (Learning Vector Quantization) performs supervised learning to classify a pattern. The feature of banknotes in HSV (Hue Saturation Value) color space is extracted in this proposed technique. The features that have been obtained are further classified using LVQ to determine the authenticity of the Rupiah banknotes. Keywords: counterfeit money; Rupiah banknotes; LVQ; HSV