MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR

Criminal acts are actions that violate the law and can arise from various factors such as emotions, psychological pressure, and others. Crime rate is a number that indicate the level of crime vulnerability in a certain area at a certain time. Higher crime rates correspond to increased vulnerability...

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Main Authors: Muhammad Althof Juniar, Azzahra Fania, Diana Ulya, Rico Ramadhan, Nur Chamidah
Format: Article
Language:English
Published: Universitas Pattimura 2024-05-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12133
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author Muhammad Althof Juniar
Azzahra Fania
Diana Ulya
Rico Ramadhan
Nur Chamidah
author_facet Muhammad Althof Juniar
Azzahra Fania
Diana Ulya
Rico Ramadhan
Nur Chamidah
author_sort Muhammad Althof Juniar
collection DOAJ
description Criminal acts are actions that violate the law and can arise from various factors such as emotions, psychological pressure, and others. Crime rate is a number that indicate the level of crime vulnerability in a certain area at a certain time. Higher crime rates correspond to increased vulnerability in an area, and vice versa. Among various forms of criminal acts, the number of criminal acts and narcotics crimes in Indonesia tends to increase in 2020 and 2021. The aim of the research is to identify the characteristics of crime rate data based on the number of decency and narcotics incidents in Indonesia using a nonparametric regression approach. This research uses a nonparametric regression method spline truncated and linear regression as comparison. It was found that West Papua Province has the highest crime rate, based on a comparison between linear regression model and truncated spline nonparametric regression model, it can be concluded that the best model is the truncated spline nonparametric regression model with a Generalized Cross Validation (GCV) of 2468.487 and a coefficient of determination of 0 .7389091, indicating that approximately 73% of the variability of the dependent variable can be explained by the independent variables included in the model.
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institution Kabale University
issn 1978-7227
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language English
publishDate 2024-05-01
publisher Universitas Pattimura
record_format Article
series Barekeng
spelling doaj-art-1d785bb2a0b0482891af8ac4f24258f02025-08-20T04:00:48ZengUniversitas PattimuraBarekeng1978-72272615-30172024-05-011821201121610.30598/barekengvol18iss2pp1201-121612133MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATORMuhammad Althof Juniar0Azzahra Fania1Diana Ulya2Rico Ramadhan3Nur Chamidah4Statistics Study Program, Faculty Science and Technology, Airlangga University, IndonesiaStatistics Study Program, Faculty Science and Technology, Airlangga University, IndonesiaStatistics Study Program, Faculty Science and Technology, Airlangga University, IndonesiaStatistics Study Program, Faculty Science and Technology, Airlangga University, IndonesiaDepartment of Mathematics, Faculty Science and Technology, Airlangga University, IndonesiaCriminal acts are actions that violate the law and can arise from various factors such as emotions, psychological pressure, and others. Crime rate is a number that indicate the level of crime vulnerability in a certain area at a certain time. Higher crime rates correspond to increased vulnerability in an area, and vice versa. Among various forms of criminal acts, the number of criminal acts and narcotics crimes in Indonesia tends to increase in 2020 and 2021. The aim of the research is to identify the characteristics of crime rate data based on the number of decency and narcotics incidents in Indonesia using a nonparametric regression approach. This research uses a nonparametric regression method spline truncated and linear regression as comparison. It was found that West Papua Province has the highest crime rate, based on a comparison between linear regression model and truncated spline nonparametric regression model, it can be concluded that the best model is the truncated spline nonparametric regression model with a Generalized Cross Validation (GCV) of 2468.487 and a coefficient of determination of 0 .7389091, indicating that approximately 73% of the variability of the dependent variable can be explained by the independent variables included in the model.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12133crime rateestimator spline truncateddecencynarcotics
spellingShingle Muhammad Althof Juniar
Azzahra Fania
Diana Ulya
Rico Ramadhan
Nur Chamidah
MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
Barekeng
crime rate
estimator spline truncated
decency
narcotics
title MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
title_full MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
title_fullStr MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
title_full_unstemmed MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
title_short MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR
title_sort modelling crime rates in indonesia using truncated spline estimator
topic crime rate
estimator spline truncated
decency
narcotics
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12133
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AT azzahrafania modellingcrimeratesinindonesiausingtruncatedsplineestimator
AT dianaulya modellingcrimeratesinindonesiausingtruncatedsplineestimator
AT ricoramadhan modellingcrimeratesinindonesiausingtruncatedsplineestimator
AT nurchamidah modellingcrimeratesinindonesiausingtruncatedsplineestimator