RA Zulfa, A Saepulrohman, L Karlitasari

Judul	:	Expert System for Early Diagnosis of Epilepsy Using the Web-Based Dempster Shafer Method
Abstrak	:	The development of information and communication technology is currently very extensive in its use, especially technology in the field of computers. Expert Systems are one of the sciences in the field of computers that can help in diagnosing various diseases, one of which is epilepsy. There are 50 million people with epilepsy in the world and of these, 125,000 die each year, and over 80% of these deaths occur in low- and middle-income countries. The expert system method used to diagnose epilepsy early is the Dempster Shafer method. The theory called Dempster Shafer provides a new method of weighting according to the facts collected. This study used 7 types of epilepsy, including in the Focal Epilepsy category consisting of Simple Partial and Complex Partial, while in the General Epilepsy category consisting of Absence, Atonic, Myoclonic, Tonic-Clonic, and Clonic. This study produces a website-based application for early diagnosis of epilepsy using the Dempster Shafer method with the PHP programming language and MySQL database. By using this application, it can provide convenience to the medical community and patients in early diagnosis of epilepsy experienced by sufferers. From the results of this study, it was found that the highest level of accuracy was found in Tonic-Clonic seizures which are included in the General Epilepsy category, namely 92.78%. Keywords:  Expert System, Early Diagnosis, Epilepsy, Epileptic, Dempster Shafer Method
Tahun	:	2024	Media Publikasi	:	Jurnal Internasional
Kategori	:	Jurnal	No/Vol/Tahun	:	3 / 5 / 2024
ISSN/ISBN	:	2722-1164
PTN/S	:	Universitas Pakuan	Program Studi	:	ILMU KOMPUTER
Bibliography	:	Anggi Mahesa, F., and Pelita Nusantara, S. (2021). Expert System for Diagnosing Epilepsy Using the Dempster Shafer Method. National Journal of Computing and Information Technology, 4(6). Anwar, H., Khan, Q. U., Nadeem, N., Pervaiz, I., Ali, M., and Cheema, F. F. (2020). Epileptic seizures. Discoveries, 8(2), e110. https://doi.org/10.15190/d.2020.7. Batubara, Hamdan. (2018). Web-based learning with Moodle version 3.4. 10.13140/RG.2.2.20230.88643. Caley, M. J., O’Leary, R. A., Fisher, R., Low-Choy, S., Johnson, S., and Mengersen, K. (2014). What is an expert? A systems perspective on expertise. Ecology and Evolution, 4(3), 231–242. https://doi.org/10.1002/ece3.926. Damodaran B, D., Salim, S., and Vargese, S. M. (2016). Performance Evaluation of MySQL and MongoDB Databases. International Journal on Cybernetics and Informatics, 5(2), 387–394. https://doi.org/10.5121/ijci.2016.5241. Fadhilah, M. R., and Triayudi, A. (2024). Application of the Dempster Shafer Method in Diagnosing Pneumonia. Scientific Study of Informatics and Computers, 4(4), 2169–2178. https://doi.org/10.30865/klik.v4i4.1734. Fadhilah, M. R., and Triayudi, A. (2024). Comparison of the Dempster Shafer Method and Certainty Factor in an Expert System for  Detecting  Coronary  Heart  Disease.  Scientific  Study  of  Informatics  and  Computers,  4(4),  2253–2261. https://doi.org/10.30865/klik.v4i4.1624. Johan, T. M. (2021). Epilepsy Detection System Using the K-Means Clustering Algorithm as an Expert System-Based Disease Detector During the Covid-19 Pandemic. TIKA Journal, 6(2), 120–130. https://doi.org/10.51179/tika.v6i02.477. Kaur, T., Diwakar, A., Kirandeep, Mirpuri, P., Tripathi, M., Chandra, P., and Gandhi, T. (2021). Artificial Intelligence in Epilepsy. In Neurology India, 69(3), 560–566. https://doi.org/10.4103/0028-3886.317233. Kusuma, R. P., and Nas, C. (2023). Expert System to Diagnose Mental Health Disorders Using the Dempster Shafer Algorithm. Journal of Information Systems and Informatics, 5(1), 391–406. https://doi.org/10.51519/journalisi.v5i1.461. Mandasari, F., Antoni, and Haramaini, T. (2022). Application of Epliepsy Diagnosis using the Certainty Factor Method at the Pinang  City  Regional  General  Hospital.  Bulletin  of  Computer  Science  Research,  2(3),  93–99. https://doi.org/10.47065/bulletincsr.v2i3.171. Muqorobin, and Nendy Akbar Rozaq Rais. (2022). Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD. International Journal of Computer and Information System, 3(3). https://ijcis.net/index.php/ijcis/index. Mustaqim, M., Rakasiwi, G., and Iskandar, A. (2024). Comparison of the Dempster Shafer Method and Bayes' Theorem for Detecting Encephalitis. Budidarma Informatics Media Journal, 8(1), 546-554. https://doi.org/10.30865/mib.v8i1.7339. Patel, S., Sayyed, A., and P.P, B. (2017). Smart Attendance Application Using Android and PHP. IJARCCE, 6(3), 226–231. https://doi.org/10.17148/ijarcce.2017.6351. Poikolainen, Karl. (1979). A comment diagnosis as a means of health forecasting. Social Science and Medicine. Part A: Medical Psychology and Medical Sociology, 13, 165-166. https://doi.org/10.1016/0271-7123(79)90023-3. Purwanti, E., Achmadi, N. W., Ernawati, and Bustomi, M. A. (2021). Expert System Using Dempster Shafer Method for Pre- Eclampsia Detection. Journal of Physics: Conference Series, 1805(1). https://doi.org/10.1088/1742-6596/1805/1/012030. Singh, Gagandeep, and Josemir W. Sander. (2020). The global burden of epilepsy report: Implications for low- and middle-income countries. Epilepsy and Behavior, 105, 1525-5050. https://doi.org/10.1016/j.yebeh.2020.106949. Susilawati, I., and Simanullang, R. Y. (2023). Expert System for Identifying ITP (Idiopathic Thrombocytopenic Purpura) using the Dempster Shafer Approach. Journal of Computer Science and Information Technology, 1(3), 17–24. Tkatek, S., Belmzoukia, A., Nafai, S., Abouchabaka, J., and Ibnou-Ratib, Y. (2020). Putting the world back to work: An expert system using big data and artificial intelligence in combating the spread of COVID-19 and similar contagious diseases. Work, 67(3), 557–572. https://doi.org/10.3233/wor-203309.
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