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All Journal Journal of Computer Networks, Architecture and High Performance Computing
Widya Tri Charisma Gultom
STIKOM Tunas Bangsa Pematangsiantar
Computer Science & IT Education

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Application of The Levenberg Marquardt Method In Predict The Amount of Criminality in Pematangsiantar City Widya Tri Charisma Gultom; Anjar Wanto; Indra Gunawan; Muhammad Ridwan Lubis; Ika Okta Kirana
Journal of Computer Networks, Architecture and High Performance Computing Vol. 3 No. 1 (2021): Computer Networks, Architecture and High Performance Computing, January 2021
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v3i1.926

Abstract

Criminality is an act that violates the law that can disturb society and even harm society both economically and psychologically. The number of crimes cannot be ascertained over time because the numbers are uncertain. So that the police have difficulty in overcoming criminal acts. With this research, the police can find out the number of criminals that will occur through the prediction that has been made. So that the police can prevent the number of criminals and increase security in Pematangsiantar city. This study uses an artificial neural network with the Levenberg Marquardt method. The research data is sourced from the Pematangsiantar Police Criminal Investigation Agency (Reskrim) in 2014-2019. The data is divided into 2 parts, namely training data and testing data. There are 5 architectural models used in this study, namely 3-30-1, 3-31-1, 3-32-1, 3-36-1 and 3-38-1. Of the 5 architectural models used, the best architecture is 3-36-1 with an accuracy rate of 85%, MSE 0.1465119, and a maximum iteration of 10000, the results obtained from the best architecture in 2020 are 85% with the number of criminals 394 people, in 2021 it is 62 % totaled 238 people, in 2022, namely 69% amounted to 170 people, so this model is good for predicting the number of crimes in Pematangsiantar City.
Co-Authors Ika Okta Kirana Indra Gunawan Muhammad Ridwan Lubis Wanto, Anjar