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All Journal International Journal of Data Science, Engineering, and Analytics (IJDASEA)
Maya Ningrum , Shavira
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Computer Science & IT Decision Sciences, Operations Research & Management

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Diagnosis of Diabetes Using Naïve Bayes Classifier Method Ardhian Nisaa , Tasya; Maya Ningrum , Shavira; Adha Haque , Berlianda
IJDASEA (International Journal of Data Science, Engineering, and Analytics) Vol. 1 No. 1 (2021): International Journal of Data Science, Engineering, and Analytics Vol 1, No 1,
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijdasea.v1i1.26

Abstract

Not a few people suffer from diabetes, diabetes is usually caused by genetic inheritance from parents and grandparents. Not only from heredity but many criteria or characteristics can determine a person has diabetes. This research was conducted by looking for a dataset on Kaggle that contains criteria for someone diagnosed or undiagnosed with diabetes such as age, gender, weakness, polyuria, polydipsia, and others. Furthermore, from these criteria, predictions are calculated using the Naive Bayes classification method where this method is one of the data mining techniques. This prediction calculation uses the Python programming language. From these criteria, each criterion is grouped with similarities and the results of the program that have been made can diagnose someone with diabetes. The prediction calculations that have been carried out have resulted in 90% accuracy, 93% precision, 89% recall, 92% specificity, and 91% F1-Score.
Co-Authors Adha Haque , Berlianda Ardhian Nisaa , Tasya