Prediksi Kerawanan Wilayah Terhadap Tindak Pencurian Sepeda Motor Menggunakan Metode (S)ARIMA Dan CART

https://doi.org/10.22146/ijccs.16643

Pradita Eko Prasetyo Utomo(1*), Azhari SN(2),

(1) Universitas gadjah mada
(2) Departemmen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


Motor vehicle theft is a crime that is most common in Indonesia. Growth of vehicle motorcycle significant in each year accompanied by the increasing theft of motorcycles in each year, we need a system that is able to forecast the development and the theft of the motorcycle.

This research proposes the development of forecasting models vulnerability criminal offense of theft of motorcycles with ARIMA forecasting method. This method not only forecast from variable of theft but also residents, vehicles and unemployment. The study also determined the classification level of vulnerability to the crime of theft of a motorcycle using a method based on the Decision Tree CART ARIMA forecasting method.

Forecasting time series data with ARIMA method performed by each of the variables to produce the best ARIMA forecasting model which varies based on the data pattern of each of those variables. The results of classification by CART method to get the value of accuracy of 92% for the city of Yogyakarta and 85% for DIY. Based on the above, the results of ARIMA forecasting and classification CART can be used in determining the level of vulnerability to the crime of theft of motorcycles.


Keywords


ARIMA, CART, vulnerability, Forecasting, Decision Tree

Full Text:

PDF


References

[1]   Badan Pusat Statistik, 2013. Statistik Kriminal. www.bps.go.id.

 

[2]   Badan Pusat Stastistik Daerah Istimewa Yogyakarta, 2015. Statistik Politik dan Keamanan.www.jogja-bps.go.id.

 

[3]   Bellaniar, M, 2014. Peramalan Demam Berdarah Dengue dengan menggunakan Metode SARIMA dan Artificial Neural Network. Thesis. UGM: Yogyakarta.

 

[4]   Chen, P., Yuan, H., and Shu, X, 2008. Forecasting Crime Using the ARIMA Model. Fifth International Conference on Fuzzy Systems and Knowledge Discovery, Jinan Shandong, 627-630.

 

[5]   Noor, N.M.M., dkk, 2011. A Framework of Decision Support for Crime Forecasting in Malaysia. Journal Recent Researches in Applied Mathematics and Informatics. ISBN: 978-1-61804-059-6.

 

[6]   Permanasari, A.E, Hidayah, I dan Bustoni, I. A, 2013. SARIMA (Seasonal ARIMA) implementation on time series to forecast the number of Malaria incidence. 2013 International Conference on Information Technology and Electrical Engineering (ICITEE), Yogyakarta, pp 203-207.

 

[7]   S. Sulistyowati and E. Winarko, “Peramalan  KLBCampakMenggunakanGabunganMetode JST Backpropagationdan CART,” IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 8, no. 1, pp. 49–58, 2014 [Online]. Available: https://jurnal.ugm.ac.id/ijccs/article/view/3495. [Accessed: 16-Mar-2017]

 

[8]   Chang, L. Y dan Wang, H,W, 2006. Analysis Of Traffic Injury Severity: An Application Of Non Parametric Classification Tree Techinques. Journal Accident Analysis Dan Prevention, Vol. 38, hal 436 – 444 diakses dari www.elsevier.com.

 

[9]   Han, J dan Kamber, M, 2001. Data Mining:Concepts And Techniques. Morgan  Kaufmann: San Fransisco, USA.

 

[10]      Kitab Undang-Undang Hukum Pidana (KUHP) Indonesia.

[11] Santoso, S, 2009. Bussiness forecasting – Metode peramalan bisnis  masa kini dengan minitab dan SPSS. Elex Media Komputindo: Jakarta.

 

[12] Rosadi, D,2014. Analisis Data Runtun Waktu dan Aplikasinya dengan R. UGM Press:Yogyakarta.

 

[13] Wei, W.W.S, 2006. Time series Analysis: Univariate and Multivariate Methods Second Edition. Pearson Addison Wesley : USA.

 

[14] Larose, D, 2005. Discovering Knowledge In Data An Introduction To Data Mining. Wiley Interscience: USA.

 

[15]      Badan Pusat Statistik, 2014. Statistik Kriminal Tahun 2014. www.bps.go.id.



DOI: https://doi.org/10.22146/ijccs.16643

Article Metrics

Abstract views : 404 | views : 370

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Indonesian Journal of Computing and Cybernetics Systems
(IJCCS) ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs


Creative Commons License
IJCCS by http://jurnal.ugm.ac.id/ijccs is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats1
View My Stats2