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Simaremare, Risky
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Application of CT-Pro Algorithm For Crime Analysis Atmaja, Eduardus Hardika Sandy; Simaremare, Risky; Rosa, Paulina Heruningsih Prima
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN XXX-XXX-XXXXX-
Publisher : Sekolah Tinggi Teknologi Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.360

Abstract

The large amount of crime data generally becomes a pile of data that lacks of information. Data mining can be implemented in various fields such as crime. Data mining techniques can be used to find information from crime data that has been collected by the police. This study analyzed 3.198 crime data of Polresta Yogyakarta in 2016-2018. This study was conducted to determine the pattern of interrelationships between regions with potential crime in the region using association rule mining with CT-PRO algorithm. System testing was done by changing support and confidence values to find best crime patterns. The results were support and confidence values that can produce association rules are 8,59% and 70% with one rule, namely: "If the committed crime is CURAT then the crime occures in MUKIM." The rule has 70,5% confidence, 275 support count and 1,66  lift ratio which means the rule were in the strong category.
Application of CT-Pro Algorithm For Crime Analysis Atmaja, Eduardus Hardika Sandy; Simaremare, Risky; Rosa, Paulina Heruningsih Prima
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.360

Abstract

The large amount of crime data generally becomes a pile of data that lacks of information. Data mining can be implemented in various fields such as crime. Data mining techniques can be used to find information from crime data that has been collected by the police. This study analyzed 3.198 crime data of Polresta Yogyakarta in 2016-2018. This study was conducted to determine the pattern of interrelationships between regions with potential crime in the region using association rule mining with CT-PRO algorithm. System testing was done by changing support and confidence values to find best crime patterns. The results were support and confidence values that can produce association rules are 8,59% and 70% with one rule, namely: "If the committed crime is CURAT then the crime occures in MUKIM." The rule has 70,5% confidence, 275 support count and 1,66  lift ratio which means the rule were in the strong category.
Co-Authors Atmaja, Eduardus Hardika Sandy Paulina H. Prima Rosa