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Analisis Keterkaitan Kejahatan×Pemodelan Medan Risiko×
BidangForensikForensik
KeluargaProcess / pipelineProcess / pipeline
Tahun asal20022011
PencetusCraig BennellJoel Caplan
TipeCrime science and offender profiling methodGeographic information systems and crime science method
Sumber perintisBennell, C., Canter, D. V., & Alison, L. J. (2002). Linking commercial burglaries by modus operandi: Tests using regression and ROC analysis. Science and Justice, 42(3), 153-164. DOI ↗Caplan, J. M., Kennedy, L. W., & Miller, J. (2011). Risk terrain modeling: Brokering criminological theory and GIS methods for crime forecasting. Journal of Research and Practice in Criminal Justice, 17(1), 56-69. link ↗
Aliascase linkage, offender linking, serial crime attributionenvironmental criminology, RTM analysis, crime risk mapping
Terkait33
RingkasanCrime linkage analysis is a forensic method that determines whether a series of crimes were committed by the same offender based on behavioral and modus operandi (MO) similarities. Developed systematically by Craig Bennell and colleagues in the early 2000s, crime linkage applies statistical and similarity-matching techniques to establish offender attribution. The method is essential in serial crime investigation, where establishing linkage enables consolidation of investigation resources, geographic profiling, and offender-focused surveillance.Risk Terrain Modeling (RTM) is a geospatial crime prediction method that identifies high-risk locations by analyzing environmental and geographic features that attract or facilitate crime. Developed by Joel Caplan, Lichen Kennedy, and James Miller in 2011, RTM bridges environmental criminology theory with geographic information systems (GIS) to create predictive risk maps. Unlike methods that predict offender location (e.g., geographic profiling), RTM predicts where crimes are likely to occur based on terrain characteristics, infrastructure, and social environmental factors.
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ScholarGateBandingkan metode: Crime Linkage Analysis · Risk Terrain Modeling. Diakses 2026-06-19 dari https://scholargate.app/id/compare