PERFORMANCE ANALYSIS OF NAÏVE BAYES ALGORITHM IN PREDICTING THE EXIT CONDITION OF STROKE PATIENTS AT DR.M. DJAMIL PADANG HOSPITAL

Rafifah Trinanda, Nurul Abdillah, Hasrinal Hasrinal

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.

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References


Airi, F. A. H., Suprapti, T., & Bahtiar, A. (2023). Comparison of Data Mining Classification Methods for Stroke Disease Prediction. E-Link: Journal of Electrical Engineering and Informatics, 18(1), 73. https://doi.org/10.30587/e-link.v18i1.5271

Fadrial, Y. E. (2021). Algoritma Naive Bayes Untuk Mencari Perkiraan Waktu Studi Mahasiswa Naive Bayes Algorithm for Finding Student Estimated Time Students. Journal of Information Technology and Computer Science (INTECOMS), 4(1), 20–29.

Handayani, T., & Feoh, G. (2019). Design of a Web-Based Medical Record Information System (Case Study at Sriati Maternity Clinic Kota Sungai TFull – Jambi). Journal of Information and Computer Technology, 2(2), 226–236. https://doi.org/10.36002/jutik.v2i2.148

Islam, U., & Syarif, N. (2023). Overview of Service Quality in Outpatient Installation at the Palangka Raya City Regional General Hospital in 2022. xviii + 136 pages + 18 tables + 25 appendices. https://repository.uinjkt.ac.id/dspace/bitstream/123456789/67607/1/Imam Syafe%27i - FIKES.pdf

Qualification, M., & Home, K. (2020). 1 , ) , 2. 11(2), 101–108.

Mauliadi, R. (2022). Journal of Informatics Business Economics Data Mining Using the K-Means Clustering Algorithm in the Analysis of Discount Rate on the Selling Price of Honda Motorcycles. 4, 7–9. https://doi.org/10.37034/infeb.v4i4.156

Murni Wijaya, W. S., & Mutaqin, Z. (2019). Application of Database Applications in School Management Activities. Journal of Educational Management, 1(2), 157–166.

Prasetyo, A., & Azis, M. S. (2021). Design of a Web-Based Medical Record Information System at the Jomin Health Center. Intercom Journal: Journal of Scientific Publications in the Field of Information and Communication Technology, 13(2), 31–38. https://doi.org/10.35969/interkom.v13i2.47

Riany, A. F., & Testiana, G. (2023). Application of Data Mining for Stroke Disease Classification Using Naïve Bayes Algorithm. Journal of SAINTEKOM, 13(1), 42–54. https://doi.org/10.33020/saintekom.v13i1.352

Saputro, I. W., & Sari, B. W. (2020). Uji Performa Algoritma Naïve Bayes untuk Prediksi Masa Studi Mahasiswa. Creative Information Technology Journal, 6(1), 1. https://doi.org/10.24076/citec.2019v6i1.178

Sidik, A. D. W. M., Himawan Kusumah, I., Suryana, A., Edwinanto, Artiyasa, M., & Pradiftha Junfithrana, A. (2020). Overview of Data Mining Classification Methods. FIDELITY : Journal of Electrical Engineering, 2(2), 34–38. https://doi.org/10.52005/fidelity.v2i2.111

Syakura, A. (2021). Overview of the risk of decubitus in stroke patients in the working area of Dr.H.Slamet Martodirdjo Pamekasan Hospital. Journal of Health Science and Technology, 2(1), 13–18. https://doi.org/10.52234/jstk.v1i1.106

Jung, A. M., Irwan, M., & Nasution, P. (2023). The importance of a Database Security System to protect personal data. JISKA: Journal of Information Systems and Informatics, 1(2), 44. http://jurnal.unidha.ac.id/index.php/jteksis

Utama, T. P., & Haibuan, M. S. (2023). Application of Naïve Bayes and Forward Selection algorithms for stroke disease prediction. Journal of Teknoinfo, 17(2), 351–357.

Wijaya, H. D., & Dwiasnati, S. (2020). Implementation of Data Mining with Naïve Bayes' Algorithm on Drug Sales. Journal of Informatics, 7(1), 1–7. https://doi.org/10.31311/ji.v7i1.6203


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