02349nam a2200313 i 4500 CSPC 20240118142354.0 240118s2023 ph a b 000 0 eng d CSPC CSPC eng UTH BSCS P215c 2023 Parel, Jodan B., author. Crime rate prediction and analysis in Iriga City using k-means algorithm / Jodan B. Parel, [and 3 others]. 152 leaves. text rdacontent unmediated rdamedia volume rdacarrier 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. Ordinario, Jason S., author Alcantara, Kyla Glen, author Alcantara, Nicole, author Onesa, Rosel O., adviser Prianes, Freddie B., panelist, chair Oñate, Joseph Jessie S., panelist Benosa, Brenda Dy-Po, panelist ddc UM 0 BSCS P215c UTH 2023 0 0 ddc 0 0 CSPC CSPC UTH 2024-01-18 0 UTH BSCS P215c 2023 006068UM 2024-01-18 00:00:00 2024-01-18 UM 26849 26849