PERFORMANCE ANALYSIS OF NAÏVE BAYES ALGORITHM IN PREDICTING THE EXIT CONDITION OF STROKE PATIENTS AT DR.M. DJAMIL PADANG HOSPITAL
Abstract
Medical record files are often just a pile of meaningless files and are not carried out further investigation to produce better services in the future. The number of strokes in Indonesia is the most common disease and ranks first in Asia, in West Sumatra the highest rate of stroke is found in Dr. M. Djamil Padang Hospital, therefore the author is interested in taking the title Performance Analysis of Naive Bayes Algorithm in Predicting the Exit Conditions of Stroke Patients at Dr. M. Djamil Padang Hospital.
The research method used is quantitative research using data mining classification, conducted from April – May 2024 with data sources derived from medical record data at Dr.M. Djamil Hospital in January, February, and March 2023. The number of population after passing the data selection process is 500 and a sample of 222 data was obtained. The sampling technique is a random sampling technique with the slovin formula. The attributes used are Age, Gender, Address, Length of Care, Care Class, Occupational Status, and Congenital Diseases.
The results of this study obtained an accuracy value of 77.48% because it produced 172 data that were correctly predicted from 222 data, while the data error value obtained was 22.52% because it produced 50 data that were incorrectly classified from 222 data.
Based on the results of the research obtained where the level of accuracy has a higher value than the error value, and is in the category of Good Clasification, it can be concluded that the performance of the Naive Algorithm in predicting the discharge condition of stroke patients at Dr. M. Djamil Padang Hospital is very good and can be implemented in hospitals and further research is carried out on other diseases.Full Text:
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