KLASIFIKASI PENYAKIT STROKE MENGGUNAKAN METODE NAIVE BAYES DAN FUZZY NAIVE BAYES BERDASARKAN RESAMPLING REPEATED SPLIT VALIDATION

NUR'AINI, FEBRIANTI DWI and Resti, Yulia and Dewi, Novi Rustiana (2023) KLASIFIKASI PENYAKIT STROKE MENGGUNAKAN METODE NAIVE BAYES DAN FUZZY NAIVE BAYES BERDASARKAN RESAMPLING REPEATED SPLIT VALIDATION. Undergraduate thesis, Sriwijaya University.

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Abstract

A stroke is a nerve funcion that results from a blockage caused by blood clots and causes the oxygen and nutrients in the brain to suffer tissue damage. This study uses the Naïve Bayes and Fuzzy Naïve Bayes method based on Repeated Split Validation Resampling and variable selection use Chi square to classify stroke disease. The data used on this research is a Stroke Prediction Dataset from Kaggle’s website. Classification of stroke disease using Naïve Bayes obtained an average Accuracy of 92,27%, Precision of 96,09%, Recall of 95.79%, and FScore of 95,94%, where here as using the naïve bayes method with chi square obtained an average Accuracy of 92,66%, Precision of 96,50%, Recall of 95.81%, and FScore of 96,16%. Classificatiion of stroke disease using Fuzzy Naïve Bayes obtained an average Accuracy of 93,15%, Precision of 97,43%, Recall of 95.46%, and FScore of 96,44%, where as using Fuzzy Naïve Bayes method with chi square obtained an average Accuracy of 93,54%, Precision of 97,74%, Recall of 95,57%, and FScore of 96,64%. Based on factors that contribute to the prediction of stroke and calculations using the Naïve Bayes and Fuzzy Naïve Bayes methods, the results are 95% not a stroke and 5% of a stroke.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Stroke, Naïve Bayes, Fuzzy Naïve Bayes, Repeated Split Validation
Subjects:	Q Science > QA Mathematics > QA1-43 General
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	Febrianti Dwi Nur'aini
Date Deposited:	22 Dec 2023 03:47
Last Modified:	22 Dec 2023 03:47
URI:	http://repository.unsri.ac.id/id/eprint/131704

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