The Conjugate Gradient Backpropagation Algorithm in Predicting Inmate Rates in Pematangsiantar City Based on Gender - Darma, Surya; Robiansyah, Wendi; Firzada, Fahmi; Irawan, Eka; Saputra, Widodo (Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa, 2024)
The increase in the number of inmates in Indonesia, particularly in Pematangsiantar City, is a significant social issue. In this context, it is important to predict inmate levels based on demographic factors, including gender. One promising approach is the use of Artificial Neural Networks (ANN) with the Backpropagation Conjugate Gradient (BPCG) algorithm. ANN is a computational model that mimics the way the human brain processes information and has been used in various applications, including crime prediction. The BPCG algorithm is a variant of the backpropagation algorithm that efficiently accelerates the convergence of ANN training. This study aims to implement ANN with the BPCG algorithm to predict inmate levels in Pematangsiantar City based on gender and to evaluate the performance of this model in the context of available crime data. MATLAB (version 7.13 R2011b) was used as a tool, employing five model architectures (7-3-1, 7-5-1, 7-11-1, 7-12-1, and 7-15-1) to test data for estimation/prediction. The best model, 7-12-1, achieved 100% accuracy with 16 iterations in less than 1 second and an MSE of 0.1477446359. With 100% accuracy, this model will be used to predict the number of inmates in Pematangsiantar City by gender in 2023. This study can make a significant contribution to the fields of criminology and data analysis and serve as a reference for future research on the use of artificial intelligence in legal and criminal contexts.