Discovering sequential disease patterns in medical databases using freespan mining and prefikspan mining approach

Rostianingsih, Silvia and Satiabudhi, Gregorius and T, LEONITA KUMALASARI (2015) Discovering sequential disease patterns in medical databases using freespan mining and prefikspan mining approach. ARPN Journal of Engineering and Applied Sciences , 9 (12). p. 2391. ISSN 1819-6608

	PDF Download (262Kb)
Preview	PDF (peerreview) Download (1074Kb) | Preview
Preview	PDF (cek plagiasi) Download (2313Kb) | Preview

Abstract

Dr. Soetomo General Hospital had computerized their system to stored inpatient#65533s history. With lots of data to be analysis, one of the needs is a decision support system in order to anticipate the spread of the disease. Therefore the hospital need a system to provide the sequential pattern of disease. One of the sequential pattern mining algorithm is pattern growth based approach. The result is sequential pattern of disease from particular area in a time period based on inpatient#65533s history. Input from user are time period, minimum support, province, and multi-dimensional. The system built with Java Net Beans 6.7 and Oracle 10g. This research showed that FreeSpan and PrefikSpan produce the same output. However, FreeSpan is more appropriate for dr. Soetomo General Hospital because the proccesing time is faster.

Actions (login required)