DISCOVERING SEQUENTIAL DISEASE PATTERNS IN MEDICAL DATABASES USING FREESPAN MINING AND PREFIKSPAN MINING APPROACH

Rostianingsih, Silvia and Satiabudhi, Gregorius and T, LEONITA KUMALASARI (2014) 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

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Abstract

Dr. Soetomo General Hospital had computerized their system to stored inpatient’s 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’s 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.

Item Type: Article
Uncontrolled Keywords: sequential pattern mining, FreeSpan, prefikSpan
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Industrial Technology > Informatics Engineering Department
Depositing User: Admin
Date Deposited: 27 Apr 2015 12:10
Last Modified: 14 Jul 2015 14:16
URI: https://repository.petra.ac.id/id/eprint/17081

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