Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri

The study focuses on developing a divorce prediction system using the Naive Bayes algorithm, a widely used classifier. The system achieved 98% accuracy in predicting divorce based on a comprehensive dataset. This approach can aid professionals in marriage counselling and family therapy to identify h...

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Main Author:	Ahmad Bakri, Alia Hannani
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Evolutionary programming (Computer science) Genetic algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/96296/1/96296.pdf
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id	my-uitm-ir.96296
record_format	uketd_dc
spelling	my-uitm-ir.962962024-06-04T07:20:31Z Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri 2024 Ahmad Bakri, Alia Hannani Evolutionary programming (Computer science). Genetic algorithms The study focuses on developing a divorce prediction system using the Naive Bayes algorithm, a widely used classifier. The system achieved 98% accuracy in predicting divorce based on a comprehensive dataset. This approach can aid professionals in marriage counselling and family therapy to identify high-risk couples and implement preventive measures. Furthermore, it can focus on enhancing the system's accuracy and applicability by expanding the dataset and incorporating more features. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96296/ https://ir.uitm.edu.my/id/eprint/96296/1/96296.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Media Abd Razak, Nor Hafizah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Abd Razak, Nor Hafizah
topic	Evolutionary programming (Computer science) Genetic algorithms
spellingShingle	Evolutionary programming (Computer science) Genetic algorithms Ahmad Bakri, Alia Hannani Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
description	The study focuses on developing a divorce prediction system using the Naive Bayes algorithm, a widely used classifier. The system achieved 98% accuracy in predicting divorce based on a comprehensive dataset. This approach can aid professionals in marriage counselling and family therapy to identify high-risk couples and implement preventive measures. Furthermore, it can focus on enhancing the system's accuracy and applicability by expanding the dataset and incorporating more features.
format	Thesis
qualification_level	Bachelor degree
author	Ahmad Bakri, Alia Hannani
author_facet	Ahmad Bakri, Alia Hannani
author_sort	Ahmad Bakri, Alia Hannani
title	Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
title_short	Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
title_full	Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
title_fullStr	Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
title_full_unstemmed	Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri
title_sort	divorce prediction using naive bayes / alia hannani ahmad bakri
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Media
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96296/1/96296.pdf
_version_	1804889984258277376

Divorce prediction using Naive Bayes / Alia Hannani Ahmad Bakri

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