ACADSTAFF UGM
| Title | : | Rule Generation for Proton Pump Inhibitor Regimen Using Learning Vector Quantization and C4.5 |
| Author | : |
Anifuddin Azis, S.Si., M.Kom. (1) Prof. Dra. Sri Hartati, M.Sc., Ph.D. (2) Drs. Edi Winarko, M.Sc.,Ph.D. (3) Prof. Dr. apt. Zullies Ikawati. (4) |
| Date | : | 0 2016 |
| Keyword | : | PPI-based drug regimen, rule generation, LVQ, C4.5 PPI-based drug regimen, rule generation, LVQ, C4.5 |
| Abstract | : | The excessive or irrational use of drugs categorized as Proton Pump Inhibitor (PPI) was indicated in Baptis Hospital of Kediri, Indonesia. In the PPI-based drug regimen among patients with digestive disorders from December 2009 to February 2010, many cases that the PPI-based drug regimen was not in accordance with the prevailing procedures were found, i.e. the drug regimen among patients who should not be given it. In this study, a method was developed to generate the PPI-based drug regimen rule. Data on the PPI-based drug regimen were trained using Learning Vector Quantization (LVQ) algorithm. The results of LVQ were stored as new data, which were extracted into IF-THEN rule with C4.5 algorithm. Based on the test, eighteen rules were generated for the PPIbased drug regimen with an accuracy rate of 82.5% on test data |
| Group of Knowledge | : | Ilmu Komputer |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
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