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

doi:10.47709/cnahpc.v3i1.926

Authors

Widya Tri Charisma Gultom STIKOM Tunas Bangsa Pematangsiantar
Anjar Wanto STIKOM Tunas Bangsa
Indra Gunawan STIKOM Tunas Bangsa
Muhammad Ridwan Lubis STIKOM Tunas Bangsa
Ika Okta Kirana STIKOM Tunas Bangsa

DOI:

10.47709/cnahpc.v3i1.926

Keywords:

Artificial Neural Networks, Levenberg Marquardt, Prediction, Total Crime

Dimension Badge Record

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.

Downloads

Download data is not yet available.

Google Scholar Cite Analysis
Abstract viewed = 207 times

References

Andriani, Y., Wanto, A., & Handrizal. (2019). Jaringan Saraf Tiruan Dalam Memprediksi Produksi Kelapa Sawit Di PT . Kre Menggunakan Algoritma Levenberg Marquardt. (September), 249–259.

Astuti, I. F., Fardinan, E., & Suyatno, A. (2016). Pemetaan Sosial Sebaran Kriminalitas Di Kota Samarinda Berbasis Single Exponential Smoothing Dan Sistem Informasi Geografis. 21–27.

Dewi, K. N. A., Bahri, S., & Irwansyah. (2019). Model Prediksi Curah Hujan Harian Menggunakan Jaringan Syaraf Tiruan Backpropagation. 2(3), 1–8.

Fardani, D. P., Wuryanto, E., & Werdiningsih, I. (2015). Sistem Pendukung Keputusan Peramalan Jumlah Kunjungan Pasien Menggunakan Metode Extreme Learning Machine (Studi Kasus: Poli Gigi Rsu Dr. Wahidin Sudiro Husodo Mojokerto). 1(1).

Giusti, A., Widodo, A. W., & Adinugroho, S. (2018). Prediksi Penjualan Mi Menggunakan Metode Extreme Learning Machine ( Elm ) Di Kober Mie Setan Cabang Soekarno Hatta. 2(8), 2972–2978.

Imneisi, I. B., & Aydin, M. (2015). Using Algorithm ( Levenberg Marquardt ) As Activation Function To Prediction Water Quality Index ( Wqi ) In Kastamonu City-Turkey.

Latief, S. A., Usmita, F., & Novarizal, R. (2016). Trends Kriminal Di Pekan Baru 2012-2016.

Mustafidah, H., Budiastanto, M. Z., & Suwarsito. (2019). Kinerja Algoritma Pelatihan Levenberg-Marquardt Dalam Variasi Banyaknya Neuron Pada Lapisan Tersembunyi (Performance Of Levenberg-Marquardt Training Algorithm Based On Variations In The Number Of Neurons In The Hidden Layer). 7(2), 115–124.

Nikentari, N. (2016). Prediksi Ketinggian Gelombang Laut Menggunakan Algoritma Levenberg Marquardt. 5(02), 34–36.

Nurrizma, E., Muliadi, M., & Sanubary, I. (2019). Analisis Kebutuhan Air Bersih Di Pdam Kota Pontianak Menggunakan Metode Levenberg Marquardt. 7(1), 8.

Primandari, A. H. (2020). Grey Double Exponential Smoothing Dengan Optimasi Levenberg-Marquardt Untuk Peramalan Volume Penumpang Di Bandara Soekarno-Hatta. 3(2), 25–39.

Ritha, N., & Retantyo, W. (2016). Implementasi Neural Fuzzy Inference System Dan Algoritma Pelatihan Levenberg-Marquardt Untuk Prediksi Curah Hujan. 10(2).

Sitompul, H. A. (2018). Optimasi Pemulusan Eksponensial Dengan Algoritma Levenberg-Marquardt Hery Andi Sitompul, S.Si, M.Si Dosen Kopertis Wilayah I Sumut, Dpk Universitas Darma Agung. Xxvi, 583–590.

Sumarauw, S. J. A. (2016). Algoritma Pelatihan Levenberg-Marquardt Backpropagation Artificial Neural Network Untuk Data Time Series. 213–222.

Zona, S. (2019). Implementasi Jaringan Syaraf Tiruan Algoritma Levenberg Marquardt Untuk Memprediksi Ketersediaan Palm Kernel Oil.