Rule Generation for Proton Pump Inhibitor Regimen Using Learning Vector Quantization and C4.5
Penulis/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)
Tanggal/Date
2016
Kata Kunci/Keyword
Abstrak/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
Rumpun Ilmu
Ilmu Komputer
Bahasa Asli/Original Language
English
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
2016-IJCSIS-rule generation for proton pump-azis hartati winarko ikawati.pdf
[PAK] Full Dokumen
2
2016-IJCSIS-rule generation for proton pump-azis hartati winarko ikawati.pdf
