ARGODI, I WAYAN ASTON (2023) IMPLEMENTASI METODE TF-IDF DAN ALGORITMA NAIVE BAYES RANDOM FOREST DALAM APLIKASI DIABETIC BERBASIS ANDROID. Undergraduate thesis, UNIVERSITAS PEMBANGUNAN NASIONAL "VETERAN" JAWA TIMUR.
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Abstract
Diabetes is a serious disease that occurs when the pancreas does not produce enough insulin to regulate blood sugar, technology could play a role important in treatment to help diagnose disease and help diabetes care management such as mobile-based applications. Method Term Frequency Inverse Document Frequency is used by counting each word presence in the document set. Naive Bayes Algorithm use probability in solving a classification case efficient and fast calculations. The Random Forest Algorithm can solve classification problems by constructing decision trees takes the majority vote for the classification. Based on this research known The Naive Bayes algorithm in this Android-based diabetic application produces accuracy of 66% with a computation time of 39 seconds with memory consumption of 80 to 351 MB, Random Forest algorithm has an advantage over the resulting accuracy of 88% in experiment using 691 training data and 71 test data, computing time taken for 14 minutes 29 seconds with a memory usage range of 136 up to 292 MB CPU usage 23 to 95%
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | I Wayan Alston Argodi | ||||||||||||
| Date Deposited: | 24 Jul 2023 07:55 | ||||||||||||
| Last Modified: | 24 Jul 2023 07:55 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/15465 |
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