| Autor: |
Haryadi, Deny, Atmaja, Dewi Marini Umi, Hakim, Arif Rahman |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 3/26/2024, Vol. 2927 Issue 1, p1-9, 9p |
| Abstrakt: |
A drug is a substance intended to be used in establishing a diagnosis, preventing, reducing, eliminating, and curing a disease or symptom of a disease. The magnitude of the drug's effectiveness depends on the dose and sensitivity of the body's organs. Accuracy in drug selection can be done in several ways, one of which is by conducting condition analysis and drug reviews to determine the effectiveness of the drugs to be used. Text Mining is one of the disciplines that can be used to extract information from a collection of documents using algorithms in Machine Learning. This research uses naïve Bayes algorithm. The dataset in this study is divided into two parts, namely 70% training and 30% test data. Based on the tests carried out in this study, the naïve Bayes algorithm produces an accuracy of 100%, which means that the algorithm can classify data very well. The accuracy results are also influenced by the amount of training data used. The more training data, the better the accuracy value that will be obtained. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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