scholarly journals Did Crime Rates Rise After Colorado Legalized Marijuana?

2016 ◽  
Vol 5 (1) ◽  
pp. 4-7
Author(s):  
Abigail D. Pohl ◽  
Samuel W. Klockenkemper ◽  
Lucas G. Carpinello ◽  
Paul M. Sommers
Keyword(s):  
Motor Vehicle ◽  
Police Department ◽  
Crime Rates ◽  
Motor Vehicle Theft ◽  
Trend Line ◽  
Vehicle Theft ◽  
Aggravated Assault ◽  
Crime Reports

Using monthly crime reports from Denver’s Police Department between January 2010 and December 2014, the authors endeavor to show if there was a break in the trend line of seven different crimes (homicide, rape, aggravated assault, burglary, robbery, larceny, and motor vehicle theft) following Colorado’s legalization of marijuana in late 2012.  After adjusting for seasonal components (some crimes tend to be higher in summer months), the trend lines reveal no break for crimes against persons.  But, three of the four trend lines for crimes against property do reveal a significant decrease after legalization.

scholarly journals TRENDS KRIMINAL DI PEKANBARU 2012-2016

2017 ◽  
Vol 2 (1) ◽  
pp. 01-19
Author(s):  
Syahrul Akmal Latief ◽  
Fakhri Usmita ◽  
Riky Novarizal
Keyword(s):  
Domestic Violence ◽  
Motor Vehicle ◽  
Crime Rates ◽  
Motor Vehicle Theft ◽  
Vehicle Theft ◽  
Wheeled Vehicles ◽  
Criminal Statistics

The least   availability of criminal data for the community, makes it difficult to get a picture of the crime. This study aims to illustrate the trend of crime in Pekanbaru City in 2012-2016 by using a quantitative alignment in view of  police criminal statistics in Pekanbaru. This study focuses on eight criminal acts, namely: theft of two-wheeled vehicles, theft by weight, maltreatment, narcotics abuse, embezzlement, domestic violence, motor vehicle theft, and deprivation. The results of this study indicate a fluctuation of crime rates for eight crimes under investigation. The crime total reached in 2014 was 928 cases, and relatively decreased for the following years. The average trend of increasing or decreasing crime amounted to 19.5 cases per year.

scholarly journals UPAYA PENANGGULANGAN TINDAK PIDANA PENCURIAN KENDARAAN BERMOTOR ANTARA HARAPAN DAN KENYATAAN

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Pratiwi Ayu Sri Daulat
Keyword(s):  
Crime Prevention ◽  
Rule Of Law ◽  
Criminal Law ◽  
Motor Vehicle ◽  
Crime Rates ◽  
Title Page ◽  
Motor Vehicle Theft ◽  
Vehicle Theft ◽  
High Crime ◽  
Short Time

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>The issue of the implementation of criminal law and crime prevention efforts is quite important for a country that wants a rule of law. Crimes that tend to increase are influenced by the coming of a multidimensional crisis. This has the potential to cause increasingly high crime rates in the community, for example motor vehicle theft has increased from year to year. Crimes committed are organized and neat enough to complicate the authorities in this case the police in uncovering cases of motorized theft. From the description above, the police try to prevent and tackle cases of motorized theft by pre-emptive, preventive and repressive measures, as an example of the causes of theft cases many factors including negligence by owners, perpetrators, and the community and there is no safety key so the perpetrator easily steals for a short time. </span></p></div></div></div>

scholarly journals Algoritma K-Means Clustering dalam Mengklasifikasi Data Daerah Rawan Tindak Kriminalitas (Polres Kepulauan Mentawai)

2021 ◽  
pp. 243-248
Author(s):  
Yoni Aswan ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Data Clustering ◽  
Clustering Algorithm ◽  
Motor Vehicle ◽  
Motor Vehicles ◽  
Hierarchical Data ◽  
Motor Vehicle Theft ◽  
Vehicle Theft ◽  
Mentawai Islands ◽  
Or Groups ◽  
Different Characteristics

Crime is all kinds of actions and actions that are economically and psychologically harmful that violate the laws in force in the State of Indonesia as well as social and religious norms. Ordinary criminal acts affect the security of the community and threaten their inner and outer peace. The research location is the Mentawai Islands Police, which is an agency that can provide security and protection for the community, especially those in the Mentawai Islands Regency. The problem is that it is difficult for the Mentawai Islands Police to classify areas that are prone to crime in the most vulnerable, moderately vulnerable and not vulnerable categories. Especially considering the condition of the Mentawai, there are four large islands consisting of 10 sub-districts, where crime is increasing every year, especially those in the Mentawai Islands Regency area such as motor vehicle theft. Based on the background of the problem above, the researcher is interested in taking research in creating a system to predict the crime rate in the Mentawai Islands Regency in order to anticipate the surge in crime that will come. The method used is the K-Means Clustering Algorithm as a non-hierarchical data clustering method to partition existing data into one or more clusters or groups. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. Clustering is one of the data mining techniques used to get groups of objects that have common characteristics in large enough data. The data used is data on cases of criminal theft of motor vehicles for the last 5 years from 2016 to 2020. The results of the test show that South Sipora District is an area prone to the crime of motor vehicle theft.

scholarly journals Could Crime Risk Be Propagated across Crime Types?

2019 ◽  
Vol 8 (5) ◽  
pp. 203 ◽  
Author(s):  
Zengli Wang ◽  
Hong Zhang
Keyword(s):  
Motor Vehicle ◽  
Motor Vehicle Theft ◽  
Vehicle Theft ◽  
Crime Type ◽  
Increased Risk ◽  
Short Period ◽  
Public Areas ◽  
Crime Types ◽  
Crime Risk ◽  
Temporal Interaction

It has long been acknowledged that crimes of the same type tend to be committed at the same location or proximity in a short period. However, the investigation of whether this phenomenon exists across crime types remains limited. The spatial-temporal clustered patterns for two types of crimes in public areas (pocket-picking and vehicle/motor vehicle theft) are separately examined. Compared with existing research, this study contributes to current research from three aspects: (1) The repeat and near-repeat phenomenon exists in two types of crimes in a large Chinese city. (2) A significant spatial-temporal interaction between pocket-picking and vehicle/motor vehicle theft exists within a range of 100 m. Some cross-crime type interactions seem to have a stronger ability of prediction than does single-crime type interaction. (3) A risk-avoiding activity is identified after spatial-temporal hotspots of another crime type. The spatial extent with increased risk is limited to a certain distance from the previous hotspots. The experimental results are analyzed and interpreted with current criminology theories.

Sign in / Sign up

Export Citation Format

Share Document