Detection of Type 2 Diabetes Mellitus Disease with Data Mining Approach Using Support Vector Machine

Tama, Bayu Adhi (2010) Detection of Type 2 Diabetes Mellitus Disease with Data Mining Approach Using Support Vector Machine. Proceeding of The 2010 International Conference on Informatics, Cybernetics, and Computer Applications (ICICCA2010). ISSN 0976-2930

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Abstract

Diabetes is a chronic disease and a major problem of morbidity and mortality in developing countries. The International Diabetes Federation (IDF) estimates that 285 million people around the world have diabetes. This total is expected to rise to 438 million within 20 years. Type 2 diabetes (TTD) is the most common type of diabetes and accounts for 90-95% of all diabetes. Detection of TTD from various factors or symptoms became an issue which was not free from false presumptions accompanied by unpredictable effects. According to this context,data mining could be used as an alternative way,help us in knowledge discovery from data. This paper utilize support vector machine (SVM) in the data mining process to acquire information from historical data of patient medical records. It offers a decision-making support through early detection of TTD for physicians and others.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science
Divisions: 09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User: Bayu Adhi Tama
Date Deposited: 25 Sep 2019 05:16
Last Modified: 25 Sep 2019 05:16
URI: http://repository.unsri.ac.id/id/eprint/8354

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