Visualisasi Aturan Asosiasi Berbasis Graph untuk Data Tindak Kejahatan

Eduardus Hardika Sandy Atmaja(1*),

(1) Program Studi Teknik Informatika, Fakultas Sains dan Teknologi, Universitas Sanata Dharma
(*) Corresponding Author

Abstract



Criminality is a social problem causing negative impacts on society welfare. Police as law enforcement officer was required to take actions to prevent criminality which was increasingly widespread. Such efforts could be realized by analizing criminal data to obtain useful information for the preparation of criminal prevention strategies. However, extracting knowledge from criminal data effectively was a problematique for them. In this study, data mining was used to solve knowledge extraction problem from the dataset. The technique was aimed to get information about crime patternsby analyzing criminal activity habits. Association rule mining and apriori algorithm were used to find crime patterns. Generating crime patterns in data mining was difficult to understand when there were too many rules. Graph based visualization of association rules designed to solve that problem. Generated visualization showed relationship between crimes. That visualization was expected to help the police to understand the crime pattern so they could do prevention efforts more effectively. The results showed that the visualization of association rules could present association rules in more interesting way and described the crime pattern.

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References


Kartono.Patologi Sosial. Jakarta: Raja Grafindo Persada. 1999.

Soesilo R.Kitab Undang-Undang Hukum Pidana serta Komentar-Komentar Lengkap Pasal Demi Pasal. Bogor: Politeia. 1985.

Fadlina.Data Mining untuk Analisa Tingkat Kejahatan Jalanan dengan Algoritma Association Rule Metode Apriori (Studi Kasus Di Polsekta Medan Sunggal). Informasi dan Teknologi Ilmiah.2014; 3(1): 144-154.

Wandi N, Hendrawan RA dan Mukhlason A.Pengembangan Sistem Rekomendasi Penelusuran Buku dengan Penggalian Association Rule Menggunakan Algoritma Apriori (Studi Kasus Badan Perpustakaan dan Kearsipan Provinsi Jawa Timur).Jurnal Teknik POMITS. 2012; 1(1): 1-5.

Tampubolon K, Saragih H dan Reza B.Implementasi Data Mining Algoritma Apriori pada Sistem Persedian AlatAlat Kesehatan.Informasi dan Teknologi Ilmiah. 2013;1(1): 93-106.

Pereira BL dan Brandao WC. ARCA: Mining Crime Patterns Using Association Rules. 11th International Conference Applied Computing. Porto. 2014: 159-165.

Hahsler M dan Chelluboina S.Visualizing Association Rules: Introduction to the R-extension Package arulesViz.Southern Methodist University.2011.

Sekhavat YA dan Hoeber O.Visualizing Association Rules using Linked Matrix Graph and Detail Views. International Journal of Intelligence Science. 2013;3:34-49.

Tan P, Steinbach M dan Kumar V.Introduction to Data Mining. Boston: Addison-Wesley. 2006.




DOI: https://doi.org/10.24071/mt.v12i1.946

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