Open AccessJaringan Syaraf Tiruan dengan Metode Learning Vector Quantization (LVQ) dalam Menentukan Klasifikasi Jenis Tilang Berdasarkan Kendaraan
Author(s) -
Winda Usman,
Irfan Sudahri Damanik,
Jaya Tata Hardinata
Publication year - 2020
Publication title -
prosiding seminar nasional riset information science (senaris)
Language(s) - English
Resource type - Journals
ISSN - 2686-0260
DOI - 10.30645/senaris.v1i0.84
Subject(s) - learning vector quantization , ticket , artificial intelligence , vector quantization , computer science , pattern recognition (psychology) , mathematics , machine learning , computer security
Learning Vector Quantization (LVQ) is a method of classifying patterns in which each output represents a particular category or class. The author uses the LVQ method to classify the type of ticket based on the vehicle that his research had previously conducted at the Simalungun District Prosecutor's Office. In this study, the author provides a solution to facilitate the filing of ticket data in the Simalungu District Prosecutor's Office, so that the data that has existing tickets can be classified according to their respective types. The results of this study indicate that LVQ is able to classify with an accuracy rate of 76.0%.