JOURNAL ARTICLE

Analisis Tingkat Kejahatan pada Anak Dibawah Umur Menggunakan Metode FP-Growth

Abstract

Crimes in minors are a series of negligence by parents who endanger or pose a dangerous threat to the child. The purpose of this study is to implement Data Mining, Association rule, and the FP-Growth Algorithm in cases of juvenile crime so that it can extract knowledge and important and interesting information from the database. The data source used is raw data that has not been processed and is a crime data on minors which are summarized in the form of reports from the West Sumatra Regional Police. The results of this study are in the form of software by analyzing data collected using the FP-Growth Algorithm and using the concept of FP-Tree development in searching for Frequent Itemset, for testing the results carried out with applications that have been designed namely the Php programming language. The results of testing are obtained from associations of crime cases that often occur in minors. So it can be seen that data mining using the FP-Growth Algorithm can be used to analyze cases of crime in minors as a material consideration for the police in order to know the ins and outs of crime in children so that it can assist the investigation process.

Keywords:
Computer science Raw data Crime analysis Juvenile delinquency Process (computing) Tree (set theory) Data mining Psychology Criminology Mathematics Programming language

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Topics

Data Mining and Machine Learning Applications
Physical Sciences →  Computer Science →  Information Systems
Multimedia Learning Systems
Physical Sciences →  Computer Science →  Information Systems
Edcuational Technology Systems
Physical Sciences →  Computer Science →  Artificial Intelligence

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