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Ni Wayan Yessy Dwijayanti 26406190

Design and Implementation Application for supporting Disease Track Record Analysis in Dr. Soetomo Hospital by Using Hybrid Dimension Association Rules Method. Ni Wayan Yessy Dwijayanti 26406190. BACKGROUND.

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Ni Wayan Yessy Dwijayanti 26406190

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  1. Design and Implementation Application for supportingDisease Track Record Analysis in Dr. Soetomo Hospital by Using Hybrid Dimension Association Rules Method Ni Wayan Yessy Dwijayanti 26406190

  2. BACKGROUND • Dr. Soetomo hospital has already used Oracle Database and Oracle Application for recording historical data patient. • The amount of medical patients are increasing every year. • The availabe data in Dr Soetomo Hospital is not compatible to provide helpful information for doctors and other medical staff on deciding specific decision.

  3. Problem Analysis • A huge amount of disease recapitulation data inhibit the information research which impact the doctors and medical staff find difficultness on taking decision for a specific problem, such as in a treatment of an illness suffered by the patient and the causes of an illness.

  4. Statement of The Problem • Dr Soetomo Hospital needs an application which provides information related to a relationship between a disease and patient data. Whether it could affected other disease or not, so the doctors and medical staff could take particular decision.

  5. Scope • Input • Dr. Soetomo medical record database. • Process • Data mining application by using Hybrid-dimension association rules method with Apriori Algorithm • Output • Rule and chart about association disease with patient data.

  6. Scope (continue) • Features • Start and end date for setting the time range. • Minimum support to generate frequent itemsets. • Patient attributes which used are gender, status,provinces, regency, education and job. • Application development is using NetBeans 6.5 • Database server using Oracle 10g • Application is tested using Dr. Soetomo medical record database.

  7. Objective • Designing and building an application at Dr SoetomoHospital in order to provide information related to association or relationship between disease and patient’s data . Whether it could affected other disease or not, so the doctors and medical staff could take particular decision.

  8. Data Mining • Data mining also known as Knowledge Discovery in Databases (KDD)which is a process to find an interesting knowledge such as pattern, association and important rules from a huge amount of data which located in a database or other saved information location. (Han, Kamber,2001)

  9. Association Rule • Association rule is a procedure to looking for a relationship between one item. • In determining the association rule is necessary to determine support and confidence to restrict whether the rule is interesting or not (Han, Kamber, 2001). • Support: A measure that indicates how much the level of dominance of an item or itemsets in the transaction.  • Confidence: A measure of the relationship between the conditional items (such as how frequently purchased item B if people buy the item A).

  10. Apriori Algorithm • Example : • With Minimum Support = 2 (Han, Kamber, 2001)

  11. Design System Aplication Context Diagram

  12. Design System Aplication DFD (Data Flow Diagram ) Level 0

  13. Generate Frequent Itemsets Flowchart

  14. Join Procedure Flowchart

  15. Scandatabase Procedure Flowchart

  16. Generate Association Rule Flowchart

  17. System Design (Menu)

  18. Output Rule

  19. Output Chart

  20. Conclusion • As a result, mining process could provide information about correlation among data (association rules) along with support information and confidence which could be analyzed. This information provide extra consideration for user in taking further decision. • This appplication could process patient data recapitulation at Dr Soetomo Hospital in order to fing frequent itemset which compatible with minimum support and resulting Hybrid Dimension Association Rules.

  21. Conclusion (continue) • The less minimum support defined and the more patient attribute used, the more itemset which occur as a result and processing time will be longer and otherwise. • The less minimum confidence, the more rules occur as a result and otherwise.

  22. Suggestion • This method expects user could complete each patient’s data with their disease which needed by this database in order to a more complete data and there’s no blank in patient data so that the given information will be more accurate.

  23. Thank You

  24. Design and Implementation Application for supportingDisease Track Record Analysis in Dr. Soetomo Hospital by Using Hybrid Dimension Association Rules Method Ni Wayan Yessy Dwijayanti 26406190

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