Ramadhani, Putri (2023) Penerapan Data Mining Untuk Klasifikasi Penyakit Diabetes Melitus Menggunakan Metode NaÏve Bayes Classifier. Other thesis, Universitas Islam Riau.

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Abstract

Diabetes mellitus is a health problem that is increasing throughout the world. The use of information technology, especially data mining, can help in the efficient identification and classification of diabetes mellitus. This research aims to apply the Naïve Bayes Classifier method in classifying diabetes mellitus based on patient data. In this research, the data used is secondary data taken from the Kaggle website. The application of data mining for the classification of diabetes mellitus using the Naïve Bayes Classifier method is expected to make a positive contribution to efforts to prevent and manage this disease. With this approach, it is hoped that early identification of high-risk patients can be carried out more efficiently, so that appropriate intervention and management can be given earlier to improve the patient's quality of life. From the test results, the system produces an accuracy of 82%.

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