Application of CT-Pro Algorithm For Crime Analysis

Eduardus Hardika Sandy Atmaja, Risky Simaremare, Paulina Heruningsih Prima Rosa

Abstract

The large amount of crime data generally becomes a pile of data that lacks of information. Data mining can be implemented in various fields such as crime. Data mining techniques can be used to find information from crime data that has been collected by the police. This study analyzed 3.198 crime data of Polresta Yogyakarta in 2016-2018. This study was conducted to determine the pattern of interrelationships between regions with potential crime in the region using association rule mining with CT-PRO algorithm. System testing was done by changing support and confidence values to find best crime patterns. The results were support and confidence values that can produce association rules are 8,59% and 70% with one rule, namely: "If the committed crime is CURAT then the crime occures in MUKIM." The rule has 70,5% confidence, 275 support count and 1,66  lift ratio which means the rule were in the strong category.

References

Moeljatno. (1993). Asas Asas Hukum Pidana. Rineka Cipta. Hal. 54.

Nagib, C. (2014). Studi Deskriptif Faktor-faktor yang Menyebabkan Terjadinya Tindak Kriminal oleh Anak-anak Di Balai Pemasyarakatan Purwokerto. Skripsi Fakultas Psikologi Universitas Muhammadiyah Purwokerto.

Badan Pusat Statistik. (2018). Statistik Kriminal 2018. Badan Pusat Statistik.

Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques 3rd Edition. Morgan Kaufmann.

Atmaja, E. H. S. (2017). Analisis Pola Tindak Kejahatan Menggunakan Visualisasi Aturan Asosiasi Berbasis Graph. Jurnal Media Teknika, 12(1), 1–66.

Fadlina. (2014). Data Mining Untuk Analisa Tingkat Kejahatan Jalanan dengan Algoritma Association Rule Metode Apriori. Jurnal Informasi Dan Teknologi Ilmiah (INTI), III(1), 144–154.

Kadafi, M. (2018). Penerapan Algoritma FP-GROWTH untuk Menemukan Pola Peminjaman Buku Perpustakaan UIN Raden Fatah Palembang. MATICS: Jurnal Ilmu Komputer Dan Teknologi Informasi, 10(2), 52–58.

Sari, N. F. A. T. (2016). Penggunaan Association Rule Mining Algoritme CT-PRO dalam Proses Penentuan Pola Tindak Kejahatan Perdagangan Manusia. Tesis Program Studi S2 Ilmu Komputer Universitas Gadjah Mada.

Tan, P., Steinbach, M., & Kumar, V. (2006). Introduction to Data Mining. Addison-Wesley.

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