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Crime rate prediction and analysis in Iriga City using k-means algorithm / Jodan B. Parel, [and 3 others].

By:

Parel, Jodan B [author.]

Contributor(s):

Material type: Text

TextDescription: 152 leavesContent type:

text

Media type:

unmediated

Carrier type:

volume

Dissertation note: Undergraduate Theses (BSCS) - Computer Science Camarines Sur Polytechnic Colleges, 2023. Abstract: Crime is the largest issue facing the entire world now and one of the greatest threats to humanity. The goal of this study is to develop a model that can be utilize in identifying and predicting the future occurrence of crime. Data on crimes committed in Iriga City between January 2018 and April 2022 was gathered and used in the study. The model employed the k-means algorithm to uncover underlying crime trends and patterns, detect crime-prone areas, and determine which barangays have the highest crime rate. The elbow method was implemented to identify the best k value in clustering. The result of the model indicates that crimes involving damage to property and physical injury had the highest rates of occurence, and of the 36 barangays im Iriga City, San Francisco (Pob.) and San Roque (Pob.) had the highest rates of crime occurrence. It was also discovered that the crime rate has been declining over time. These findings will be very useful to law enforcement and local government units in taking necessary actions to reduce crime and in crafting safety and security policies. Moreover, the developed model can be a springboard for the future development of more reliable crime prediction and analysis applications.

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Item type	Current library	Shelving location	Call number	Status	Date due	Barcode
Unpublished Materials	Main Library	Undergraduate Thesis Section	UTH BSCS P215c 2023 (Browse shelf(Opens below))	Not for loan		006068UM

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Previous	UTH BSCS Oc12s 2021 Student career path tracer for BSIT and BSCS using expectation-maximization algorithm	UTH BSCS P129q 2017 Query optimization variance between postgresql and mysql/	UTH BSCS P167c 2019 Comparative study between RSA and AES algorithm in terms of digital image encryption	UTH BSCS P215c 2023 Crime rate prediction and analysis in Iriga City using k-means algorithm / Jodan B. Parel, [and 3 others].	UTH BSCS P223r 2024 Real-time Filipino sign language to text translation using region-based convolutional neural network /	UTH BSCS P832 2017 Room scheduling using greedy algorithm/	UTH BSCS Q61s 2024 Securenet: a deep learning paradigm for network security against DDOS attacks /	Next

Undergraduate Theses (BSCS) - Computer Science Camarines Sur Polytechnic Colleges, 2023.

Includes bibliographical references.

Crime is the largest issue facing the entire world now and one of the greatest threats to humanity. The goal of this study is to develop a model that can be utilize in identifying and predicting the future occurrence of crime. Data on crimes committed in Iriga City between January 2018 and April 2022 was gathered and used in the study. The model employed the k-means algorithm to uncover underlying crime trends and patterns, detect crime-prone areas, and determine which barangays have the highest crime rate. The elbow method was implemented to identify the best k value in clustering. The result of the model indicates that crimes involving damage to property and physical injury had the highest rates of occurence, and of the 36 barangays im Iriga City, San Francisco (Pob.) and San Roque (Pob.) had the highest rates of crime occurrence. It was also discovered that the crime rate has been declining over time. These findings will be very useful to law enforcement and local government units in taking necessary actions to reduce crime and in crafting safety and security policies. Moreover, the developed model can be a springboard for the future development of more reliable crime prediction and analysis applications.

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