Crime rate visualization with predictive analytics

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creativework.keywordscrime rate, machine learning algorithms
dc.contributor.advisorPimentel, Emmalou B.
dc.contributor.authorBuncab, Lorenzo Manuel P.
dc.contributor.authorSandoval, Jean Steven F.
dc.contributor.authorOcampo, Jan Lander T.
dc.contributor.authorAlmodovar, Averry Dennisson A.
dc.contributor.chairMique Jr., Eusebio L.
dc.contributor.committeememberGallardo, Bernabe P.
dc.contributor.committeememberLedda, Mark Kristian C.
dc.date.accessioned2026-03-11T06:15:12Z
dc.date.available2026-03-11T06:15:12Z
dc.date.issued2024-05
dc.descriptionFull text
dc.description.abstractThis research utilized advanced machine learning models and artificial intelligence neural networks to develop and integrate a system for predicting and visualizing crime rate data in specific areas. Partnering with a government organization, the researchers carefully selected respondents to ensure comprehensive data collection. The development process presented numerous challenges, providing valuable learning experiences. Geographic Information System (GIS) graphs and heatmaps enhanced the system's efficacy and reliability. The study achieved the following objectives: identifying crime prediction indicators, training machine learning models, developing the crime prediction system using CRISP-DM methodology, and testing the system with the User Acceptance Test (UAT) and System Usability Scale (SUS) with six police personnel and four IT experts from DMMMSU MLUC. Significant findings included the identification of dataset indicators from San Juan Police Station data, the high accuracy of regression models, successful integration using the Flask API framework, and a 100% acceptability rate from UAT and 95% from SUS
dc.format.extentxi, 48 p.: ill. (col.).
dc.identifier.citationBuncab, L. M. P., Sandoval, J. S. F., Ocampo, J. L. T., & Almodovar, A. D. A. (2024). Crime rate visualization with predictive analytics. [Unpublished Undergraduate Thesis]. Don Mariano Marcos Memorial State University - Mid La Union Campus, City of San Fernando, La Union. Lakasa ti Sirib, DMMMSU Institutional Repository.
dc.identifier.urihttps://lakasa.dmmmsu.edu.ph/handle/123456789/1176
dc.language.isoEnglish
dc.publisherDon Mariano Marcos Memorial State University - Mid La Union Campus
dc.rights.licenseCC BY 4.0
dc.sdgSDG 16
dc.subjectCrime
dc.subjectCriminal investigation
dc.subjectCrime prevention
dc.subjectReinforcement learning (Machine learning)[
dc.subjectMachine learning
dc.subjectMachine learning--Mathematical models
dc.subjectMachine learning--Statistical methods
dc.subjectMachine learning--Industrial applications
dc.subjectMachine learning--Technique
dc.subjectMachine learning--Graphic methods
dc.subjectMachine learning--Study and teaching
dc.subjectSimulated annealing (Mathematics)
dc.subjectComputer algorithms
dc.titleCrime rate visualization with predictive analytics
dc.typeThesis
dcterms.accessRightsOpen access
thesis.degree.disciplineCollege of Information Technology
thesis.degree.levelUndergraduate
thesis.degree.nameBachelor of Science in Information Technology
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