범죄 발생에 대한 계절요인 분석

Abstract

The purpose of this study is to contribute to crime prevention and policing policies through deriving seasonal cycle and monthly seasonal factors of major crime, such as murder, robbery, burglary, rape, violence, etc. In order to achieve this purpose, Sequential Chart of Time Series(N), Autocorrelation Analysis of Time Series(A), Seasonal Decomposition of Time Series(S) was performed. The following is the result of the study. Murder crime is in progress a cycle of 12 months in the analysis Autocorrelation Function and its Seasonal factors are in August(118.0%), July(116.9%), September(115.3%), May(108.8%), October(106.0%), June(104.1%), April(102.9%), March(96.7%), November(86.9%), December(86.1%), January(80.1%) and February(78.2%). Robbery crime is in progress a cycle of 12 months in the analysis Autocorrelation Function and its Seasonal factors are in May(136.2%), April (120.1%), March 112.1%), September(108.9%), October(102.6%), June(98.5%), July(98.1%), August(97.4%), February(82.4%), January(81.7%), November(81.6%), and December(80.5%). Burglary crime is in progress a cycle of 12 months in the analysis Autocorrelation Function and its Seasonal factors are in May(116.0%), October(109.5%), September(108.6%), June(107.2%), November(103.0%), December(103.0%), April(102.6%), July(102.6%), August(100.4%), March(96.6%), January(75.4%), and February(75.1%). Rape crime is in progress a cycle of 12 months in the analysis Autocorrelation Function and its Seasonal factors are in July(117.9%), May(114%), August(113.8%), September(113.2%), June(109.2%), October(109.2%), April(97.2%), 11month(96.4%), March(92.6%), December(88.2%), January(77.2%), and February(71.3%). Violence crime is in progress a cycle of 12 months in the analysis Autocorrelation Function and its Seasonal factors are in October(109.7%), July(109.1%), September(107.5%), June(105.7%), August(104.7%), May(103.2%), November(101.1%), December(96.7%), March(95.7%), April(94.9%), January(91.9%) and February(79.8%).